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2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 7239</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: non-Intrusive speech evaluation</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7239</span> Development of Non-Intrusive Speech Evaluation Measure Using S-Transform and Light-Gbm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tusar%20Kanti%20Dash">Tusar Kanti Dash</a>, <a href="https://publications.waset.org/abstracts/search?q=Ganapati%20Panda"> Ganapati Panda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The evaluation of speech quality and intelligence is critical to the overall effectiveness of the Speech Enhancement Algorithms. Several intrusive and non-intrusive measures are employed to calculate these parameters. Non-Intrusive Evaluation is most challenging as, very often, the reference clean speech data is not available. In this paper, a novel non-intrusive speech evaluation measure is proposed using audio features derived from the Stockwell transform. These features are used with the Light Gradient Boosting Machine for the effective prediction of speech quality and intelligibility. The proposed model is analyzed using noisy and reverberant speech from four databases, and the results are compared with the standard Intrusive Evaluation Measures. It is observed from the comparative analysis that the proposed model is performing better than the standard Non-Intrusive models. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=non-Intrusive%20speech%20evaluation" title="non-Intrusive speech evaluation">non-Intrusive speech evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=S-transform" title=" S-transform"> S-transform</a>, <a href="https://publications.waset.org/abstracts/search?q=light%20GBM" title=" light GBM"> light GBM</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20quality" title=" speech quality"> speech quality</a>, <a href="https://publications.waset.org/abstracts/search?q=and%20intelligibility" title=" and intelligibility"> and intelligibility</a> </p> <a href="https://publications.waset.org/abstracts/139626/development-of-non-intrusive-speech-evaluation-measure-using-s-transform-and-light-gbm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/139626.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">267</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7238</span> Performance Evaluation of Acoustic-Spectrographic Voice Identification Method in Native and Non-Native Speech</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=E.%20Krasnova">E. Krasnova</a>, <a href="https://publications.waset.org/abstracts/search?q=E.%20Bulgakova"> E. Bulgakova</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20Shchemelinin"> V. Shchemelinin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper deals with acoustic-spectrographic voice identification method in terms of its performance in non-native language speech. Performance evaluation is conducted by comparing the result of the analysis of recordings containing native language speech with recordings that contain foreign language speech. Our research is based on Tajik and Russian speech of Tajik native speakers due to the character of the criminal situation with drug trafficking. We propose a pilot experiment that represents a primary attempt enter the field. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=speaker%20identification" title="speaker identification">speaker identification</a>, <a href="https://publications.waset.org/abstracts/search?q=acoustic-spectrographic%20method" title=" acoustic-spectrographic method"> acoustic-spectrographic method</a>, <a href="https://publications.waset.org/abstracts/search?q=non-native%20speech" title=" non-native speech"> non-native speech</a>, <a href="https://publications.waset.org/abstracts/search?q=performance%20evaluation" title=" performance evaluation"> performance evaluation</a> </p> <a href="https://publications.waset.org/abstracts/12496/performance-evaluation-of-acoustic-spectrographic-voice-identification-method-in-native-and-non-native-speech" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/12496.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">449</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7237</span> Blind Speech Separation Using SRP-PHAT Localization and Optimal Beamformer in Two-Speaker Environments</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hai%20Quang%20Hong%20Dam">Hai Quang Hong Dam</a>, <a href="https://publications.waset.org/abstracts/search?q=Hai%20Ho"> Hai Ho</a>, <a href="https://publications.waset.org/abstracts/search?q=Minh%20Hoang%20Le%20Ngo"> Minh Hoang Le Ngo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper investigates the problem of blind speech separation from the speech mixture of two speakers. A voice activity detector employing the Steered Response Power - Phase Transform (SRP-PHAT) is presented for detecting the activity information of speech sources and then the desired speech signals are extracted from the speech mixture by using an optimal beamformer. For evaluation, the algorithm effectiveness, a simulation using real speech recordings had been performed in a double-talk situation where two speakers are active all the time. Evaluations show that the proposed blind speech separation algorithm offers a good interference suppression level whilst maintaining a low distortion level of the desired signal. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=blind%20speech%20separation" title="blind speech separation">blind speech separation</a>, <a href="https://publications.waset.org/abstracts/search?q=voice%20activity%20detector" title=" voice activity detector"> voice activity detector</a>, <a href="https://publications.waset.org/abstracts/search?q=SRP-PHAT" title=" SRP-PHAT"> SRP-PHAT</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20beamformer" title=" optimal beamformer"> optimal beamformer</a> </p> <a href="https://publications.waset.org/abstracts/53263/blind-speech-separation-using-srp-phat-localization-and-optimal-beamformer-in-two-speaker-environments" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/53263.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">288</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7236</span> Comparative Methods for Speech Enhancement and the Effects on Text-Independent Speaker Identification Performance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Ajgou">R. Ajgou</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Sbaa"> S. Sbaa</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Ghendir"> S. Ghendir</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Chemsa"> A. Chemsa</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Taleb-Ahmed"> A. Taleb-Ahmed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The speech enhancement algorithm is to improve speech quality. In this paper, we review some speech enhancement methods and we evaluated their performance based on Perceptual Evaluation of Speech Quality scores (PESQ, ITU-T P.862). All method was evaluated in presence of different kind of noise using TIMIT database and NOIZEUS noisy speech corpus.. The noise was taken from the AURORA database and includes suburban train noise, babble, car, exhibition hall, restaurant, street, airport and train station noise. Simulation results showed improved performance of speech enhancement for Tracking of non-stationary noise approach in comparison with various methods in terms of PESQ measure. Moreover, we have evaluated the effects of the speech enhancement technique on Speaker Identification system based on autoregressive (AR) model and Mel-frequency Cepstral coefficients (MFCC). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=speech%20enhancement" title="speech enhancement">speech enhancement</a>, <a href="https://publications.waset.org/abstracts/search?q=pesq" title=" pesq"> pesq</a>, <a href="https://publications.waset.org/abstracts/search?q=speaker%20recognition" title=" speaker recognition"> speaker recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=MFCC" title=" MFCC"> MFCC</a> </p> <a href="https://publications.waset.org/abstracts/31102/comparative-methods-for-speech-enhancement-and-the-effects-on-text-independent-speaker-identification-performance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31102.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">428</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7235</span> Automatic Speech Recognition Systems Performance Evaluation Using Word Error Rate Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jo%C3%A3o%20Rato">João Rato</a>, <a href="https://publications.waset.org/abstracts/search?q=Nuno%20Costa"> Nuno Costa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The human verbal communication is a two-way process which requires a mutual understanding that will result in some considerations. This kind of communication, also called dialogue, besides the supposed human agents it can also be performed between human agents and machines. The interaction between Men and Machines, by means of a natural language, has an important role concerning the improvement of the communication between each other. Aiming at knowing the performance of some speech recognition systems, this document shows the results of the accomplished tests according to the Word Error Rate evaluation method. Besides that, it is also given a set of information linked to the systems of Man-Machine communication. After this work has been made, conclusions were drawn regarding the Speech Recognition Systems, among which it can be mentioned their poor performance concerning the voice interpretation in noisy environments. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=automatic%20speech%20recognition" title="automatic speech recognition">automatic speech recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=man-machine%20conversation" title=" man-machine conversation"> man-machine conversation</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20recognition" title=" speech recognition"> speech recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=spoken%20dialogue%20systems" title=" spoken dialogue systems"> spoken dialogue systems</a>, <a href="https://publications.waset.org/abstracts/search?q=word%20error%20rate" title=" word error rate"> word error rate</a> </p> <a href="https://publications.waset.org/abstracts/62274/automatic-speech-recognition-systems-performance-evaluation-using-word-error-rate-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62274.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">326</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7234</span> Robust Noisy Speech Identification Using Frame Classifier Derived Features</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Punnoose%20A.%20K.">Punnoose A. K.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an approach for identifying noisy speech recording using a multi-layer perception (MLP) trained to predict phonemes from acoustic features. Characteristics of the MLP posteriors are explored for clean speech and noisy speech at the frame level. Appropriate density functions are used to fit the softmax probability of the clean and noisy speech. A function that takes into account the ratio of the softmax probability density of noisy speech to clean speech is formulated. These phoneme independent scoring is weighted using a phoneme-specific weightage to make the scoring more robust. Simple thresholding is used to identify the noisy speech recording from the clean speech recordings. The approach is benchmarked on standard databases, with a focus on precision. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=noisy%20speech%20identification" title="noisy speech identification">noisy speech identification</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20pre-processing" title=" speech pre-processing"> speech pre-processing</a>, <a href="https://publications.waset.org/abstracts/search?q=noise%20robustness" title=" noise robustness"> noise robustness</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20engineering" title=" feature engineering"> feature engineering</a> </p> <a href="https://publications.waset.org/abstracts/144694/robust-noisy-speech-identification-using-frame-classifier-derived-features" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/144694.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">134</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7233</span> Multi-Granularity Feature Extraction and Optimization for Pathological Speech Intelligibility Evaluation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chunying%20Fang">Chunying Fang</a>, <a href="https://publications.waset.org/abstracts/search?q=Haifeng%20Li"> Haifeng Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Lin%20Ma"> Lin Ma</a>, <a href="https://publications.waset.org/abstracts/search?q=Mancai%20Zhang"> Mancai Zhang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Speech intelligibility assessment is an important measure to evaluate the functional outcomes of surgical and non-surgical treatment, speech therapy and rehabilitation. The assessment of pathological speech plays an important role in assisting the experts. Pathological speech usually is non-stationary and mutational, in this paper, we describe a multi-granularity combined feature schemes, and which is optimized by hierarchical visual method. First of all, the difference granularity level pathological features are extracted which are BAFS (Basic acoustics feature set), local spectral characteristics MSCC (Mel s-transform cepstrum coefficients) and nonlinear dynamic characteristics based on chaotic analysis. Latterly, radar chart and F-score are proposed to optimize the features by the hierarchical visual fusion. The feature set could be optimized from 526 to 96-dimensions.The experimental results denote that new features by support vector machine (SVM) has the best performance, with a recognition rate of 84.4% on NKI-CCRT corpus. The proposed method is thus approved to be effective and reliable for pathological speech intelligibility evaluation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=pathological%20speech" title="pathological speech">pathological speech</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-granularity%20feature" title=" multi-granularity feature"> multi-granularity feature</a>, <a href="https://publications.waset.org/abstracts/search?q=MSCC%20%28Mel%20s-transform%20cepstrum%20coefficients%29" title=" MSCC (Mel s-transform cepstrum coefficients)"> MSCC (Mel s-transform cepstrum coefficients)</a>, <a href="https://publications.waset.org/abstracts/search?q=F-score" title=" F-score"> F-score</a>, <a href="https://publications.waset.org/abstracts/search?q=radar%20chart" title=" radar chart"> radar chart</a> </p> <a href="https://publications.waset.org/abstracts/52914/multi-granularity-feature-extraction-and-optimization-for-pathological-speech-intelligibility-evaluation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52914.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">285</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7232</span> An Analysis of Illocutioary Act in Martin Luther King Jr.'s Propaganda Speech Entitled 'I Have a Dream'</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahgfirah%20Firdaus%20Soberatta">Mahgfirah Firdaus Soberatta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Language cannot be separated from human life. Humans use language to convey ideas, thoughts, and feelings. We can use words for different things for example like asserted, advising, promise, give opinions, hopes, etc. Propaganda is an attempt which seeks to obtain stable behavior to adopt everyone to his everyday life. It also controls the thoughts and attitudes of individuals in social settings permanent. In this research, the writer will discuss about the speech act in a propaganda speech delivered by Martin Luther King Jr. in Washington at Lincoln Memorial on August 28, 1963. 'I Have a Dream' is a public speech delivered by American civil rights activist MLK, he calls from an end to racism in USA. In this research, the writer uses Searle theory to analyze the types of illocutionary speech act that used by Martin Luther King Jr. in his propaganda speech. In this research, the writer uses a qualitative method described in descriptive, because the research wants to describe and explain the types of illocutionary speech acts used by Martin Luther King Jr. in his propaganda speech. The findings indicate that there are five types of speech acts in Martin Luther King Jr. speech. MLK also used direct speech and indirect speech in his propaganda speech. However, direct speech is the dominant speech act that MLK used in his propaganda speech. It is hoped that this research is useful for the readers to enrich their knowledge in a particular field of pragmatic speech acts. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=speech%20act" title="speech act">speech act</a>, <a href="https://publications.waset.org/abstracts/search?q=propaganda" title=" propaganda"> propaganda</a>, <a href="https://publications.waset.org/abstracts/search?q=Martin%20Luther%20King%20Jr." title=" Martin Luther King Jr."> Martin Luther King Jr.</a>, <a href="https://publications.waset.org/abstracts/search?q=speech" title=" speech"> speech</a> </p> <a href="https://publications.waset.org/abstracts/45649/an-analysis-of-illocutioary-act-in-martin-luther-king-jrs-propaganda-speech-entitled-i-have-a-dream" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/45649.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">448</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7231</span> A Novel RLS Based Adaptive Filtering Method for Speech Enhancement</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pogula%20Rakesh">Pogula Rakesh</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Kishore%20Kumar"> T. Kishore Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Speech enhancement is a long standing problem with numerous applications like teleconferencing, VoIP, hearing aids, and speech recognition. The motivation behind this research work is to obtain a clean speech signal of higher quality by applying the optimal noise cancellation technique. Real-time adaptive filtering algorithms seem to be the best candidate among all categories of the speech enhancement methods. In this paper, we propose a speech enhancement method based on Recursive Least Squares (RLS) adaptive filter of speech signals. Experiments were performed on noisy data which was prepared by adding AWGN, Babble and Pink noise to clean speech samples at -5dB, 0dB, 5dB, and 10dB SNR levels. We then compare the noise cancellation performance of proposed RLS algorithm with existing NLMS algorithm in terms of Mean Squared Error (MSE), Signal to Noise ratio (SNR), and SNR loss. Based on the performance evaluation, the proposed RLS algorithm was found to be a better optimal noise cancellation technique for speech signals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20filter" title="adaptive filter">adaptive filter</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20noise%20canceller" title=" adaptive noise canceller"> adaptive noise canceller</a>, <a href="https://publications.waset.org/abstracts/search?q=mean%20squared%20error" title=" mean squared error"> mean squared error</a>, <a href="https://publications.waset.org/abstracts/search?q=noise%20reduction" title=" noise reduction"> noise reduction</a>, <a href="https://publications.waset.org/abstracts/search?q=NLMS" title=" NLMS"> NLMS</a>, <a href="https://publications.waset.org/abstracts/search?q=RLS" title=" RLS"> RLS</a>, <a href="https://publications.waset.org/abstracts/search?q=SNR" title=" SNR"> SNR</a>, <a href="https://publications.waset.org/abstracts/search?q=SNR%20loss" title=" SNR loss"> SNR loss</a> </p> <a href="https://publications.waset.org/abstracts/16212/a-novel-rls-based-adaptive-filtering-method-for-speech-enhancement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16212.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">486</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7230</span> Dual-Channel Multi-Band Spectral Subtraction Algorithm Dedicated to a Bilateral Cochlear Implant</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fathi%20Kallel">Fathi Kallel</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Ben%20Hamida"> Ahmed Ben Hamida</a>, <a href="https://publications.waset.org/abstracts/search?q=Christian%20Berger-Vachon"> Christian Berger-Vachon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a Speech Enhancement Algorithm based on Multi-Band Spectral Subtraction (MBSS) principle is evaluated for Bilateral Cochlear Implant (BCI) users. Specifically, dual-channel noise power spectral estimation algorithm using Power Spectral Densities (PSD) and Cross Power Spectral Densities (CPSD) of the observed signals is studied. The enhanced speech signal is obtained using Dual-Channel Multi-Band Spectral Subtraction ‘DC-MBSS’ algorithm. For performance evaluation, objective speech assessment test relying on Perceptual Evaluation of Speech Quality (PESQ) score is performed to fix the optimal number of frequency bands needed in DC-MBSS algorithm. In order to evaluate the speech intelligibility, subjective listening tests are assessed with 3 deafened BCI patients. Experimental results obtained using French Lafon database corrupted by an additive babble noise at different Signal-to-Noise Ratios (SNR) showed that DC-MBSS algorithm improves speech understanding for single and multiple interfering noise sources. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=speech%20enhancement" title="speech enhancement">speech enhancement</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20substracion" title=" spectral substracion"> spectral substracion</a>, <a href="https://publications.waset.org/abstracts/search?q=noise%20estimation" title=" noise estimation"> noise estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=cochlear%20impalnt" title=" cochlear impalnt"> cochlear impalnt</a> </p> <a href="https://publications.waset.org/abstracts/18785/dual-channel-multi-band-spectral-subtraction-algorithm-dedicated-to-a-bilateral-cochlear-implant" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18785.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">554</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7229</span> The Online Advertising Speech that Effect to the Thailand Internet User Decision Making</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Panprae%20Bunyapukkna">Panprae Bunyapukkna</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study investigated figures of speech used in fragrance advertising captions on the Internet. The objectives of the study were to find out the frequencies of figures of speech in fragrance advertising captions and the types of figures of speech most commonly applied in captions. The relation between figures of speech and fragrance was also examined in order to analyze how figures of speech were used to represent fragrance. Thirty-five fragrance advertisements were randomly selected from the Internet. Content analysis was applied in order to consider the relation between figures of speech and fragrance. The results showed that figures of speech were found in almost every fragrance advertisement except one advertisement of Lancôme. Thirty-four fragrance advertising captions used at least one kind of figure of speech. Metaphor was most frequently found and also most frequently applied in fragrance advertising captions, followed by alliteration, rhyme, simile and personification, and hyperbole respectively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=advertising%20speech" title="advertising speech">advertising speech</a>, <a href="https://publications.waset.org/abstracts/search?q=fragrance%20advertisements" title=" fragrance advertisements"> fragrance advertisements</a>, <a href="https://publications.waset.org/abstracts/search?q=figures%20of%20speech" title=" figures of speech"> figures of speech</a>, <a href="https://publications.waset.org/abstracts/search?q=metaphor" title=" metaphor"> metaphor</a> </p> <a href="https://publications.waset.org/abstracts/44259/the-online-advertising-speech-that-effect-to-the-thailand-internet-user-decision-making" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44259.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">244</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7228</span> Combined Automatic Speech Recognition and Machine Translation in Business Correspondence Domain for English-Croatian</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sanja%20Seljan">Sanja Seljan</a>, <a href="https://publications.waset.org/abstracts/search?q=Ivan%20Dun%C4%91er"> Ivan Dunđer</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper presents combined automatic speech recognition (ASR) for English and machine translation (MT) for English and Croatian in the domain of business correspondence. The first part presents results of training the ASR commercial system on two English data sets, enriched by error analysis. The second part presents results of machine translation performed by online tool Google Translate for English and Croatian and Croatian-English language pairs. Human evaluation in terms of usability is conducted and internal consistency calculated by Cronbach's alpha coefficient, enriched by error analysis. Automatic evaluation is performed by WER (Word Error Rate) and PER (Position-independent word Error Rate) metrics, followed by investigation of Pearson’s correlation with human evaluation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=automatic%20machine%20translation" title="automatic machine translation">automatic machine translation</a>, <a href="https://publications.waset.org/abstracts/search?q=integrated%20language%20technologies" title=" integrated language technologies"> integrated language technologies</a>, <a href="https://publications.waset.org/abstracts/search?q=quality%20evaluation" title=" quality evaluation"> quality evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20recognition" title=" speech recognition"> speech recognition</a> </p> <a href="https://publications.waset.org/abstracts/11845/combined-automatic-speech-recognition-and-machine-translation-in-business-correspondence-domain-for-english-croatian" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11845.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">488</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7227</span> TeleMe Speech Booster: Web-Based Speech Therapy and Training Program for Children with Articulation Disorders</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=C.%20Treerattanaphan">C. Treerattanaphan</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Boonpramuk"> P. Boonpramuk</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Singla"> P. Singla</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Frequent, continuous speech training has proven to be a necessary part of a successful speech therapy process, but constraints of traveling time and employment dispensation become key obstacles especially for individuals living in remote areas or for dependent children who have working parents. In order to ameliorate speech difficulties with ample guidance from speech therapists, a website has been developed that supports speech therapy and training for people with articulation disorders in the standard Thai language. This web-based program has the ability to record speech training exercises for each speech trainee. The records will be stored in a database for the speech therapist to investigate, evaluate, compare and keep track of all trainees’ progress in detail. Speech trainees can request live discussions via video conference call when needed. Communication through this web-based program facilitates and reduces training time in comparison to walk-in training or appointments. This type of training also allows people with articulation disorders to practice speech lessons whenever or wherever is convenient for them, which can lead to a more regular training processes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=web-based%20remote%20training%20program" title="web-based remote training program">web-based remote training program</a>, <a href="https://publications.waset.org/abstracts/search?q=Thai%20speech%20therapy" title=" Thai speech therapy"> Thai speech therapy</a>, <a href="https://publications.waset.org/abstracts/search?q=articulation%20disorders" title=" articulation disorders"> articulation disorders</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20booster" title=" speech booster"> speech booster</a> </p> <a href="https://publications.waset.org/abstracts/13916/teleme-speech-booster-web-based-speech-therapy-and-training-program-for-children-with-articulation-disorders" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13916.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">384</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7226</span> Annexation (Al-Iḍāfah) in Thariq bin Ziyad’s Speech</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Annisa%20D.%20Febryandini">Annisa D. Febryandini</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Annexation is a typical construction that commonly used in Arabic language. The use of the construction appears in Arabic speech such as the speech of Thariq bin Ziyad. The speech as one of the most famous speeches in the history of Islam uses many annexations. This qualitative research paper uses the secondary data by library method. Based on the data, this paper concludes that the speech has two basic structures with some variations and has some grammatical relationship. Different from the other researches that identify the speech in sociology field, the speech in this paper will be analyzed in linguistic field to take a look at the structure of its annexation as well as the grammatical relationship. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=annexation" title="annexation">annexation</a>, <a href="https://publications.waset.org/abstracts/search?q=Thariq%20bin%20Ziyad" title=" Thariq bin Ziyad"> Thariq bin Ziyad</a>, <a href="https://publications.waset.org/abstracts/search?q=grammatical%20relationship" title=" grammatical relationship"> grammatical relationship</a>, <a href="https://publications.waset.org/abstracts/search?q=Arabic%20syntax" title=" Arabic syntax"> Arabic syntax</a> </p> <a href="https://publications.waset.org/abstracts/72847/annexation-al-iafah-in-thariq-bin-ziyads-speech" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72847.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">332</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7225</span> Effect of Noise Reduction Algorithms on Temporal Splitting of Speech Signal to Improve Speech Perception for Binaural Hearing Aids</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rajani%20S.%20Pujar">Rajani S. Pujar</a>, <a href="https://publications.waset.org/abstracts/search?q=Pandurangarao%20N.%20Kulkarni"> Pandurangarao N. Kulkarni</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Increased temporal masking affects the speech perception in persons with sensorineural hearing impairment especially under adverse listening conditions. This paper presents a cascaded scheme, which employs a noise reduction algorithm as well as temporal splitting of the speech signal. Earlier investigations have shown that by splitting the speech temporally and presenting alternate segments to the two ears help in reducing the effect of temporal masking. In this technique, the speech signal is processed by two fading functions, complementary to each other, and presented to left and right ears for binaural dichotic presentation. In the present study, half cosine signal is used as a fading function with crossover gain of 6 dB for the perceptual balance of loudness. Temporal splitting is combined with noise reduction algorithm to improve speech perception in the background noise. Two noise reduction schemes, namely spectral subtraction and Wiener filter are used. Listening tests were conducted on six normal-hearing subjects, with sensorineural loss simulated by adding broadband noise to the speech signal at different signal-to-noise ratios (∞, 3, 0, and -3 dB). Objective evaluation using PESQ was also carried out. The MOS score for VCV syllable /asha/ for SNR values of ∞, 3, 0, and -3 dB were 5, 4.46, 4.4 and 4.05 respectively, while the corresponding MOS scores for unprocessed speech were 5, 1.2, 0.9 and 0.65, indicating significant improvement in the perceived speech quality for the proposed scheme compared to the unprocessed speech. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=MOS" title="MOS">MOS</a>, <a href="https://publications.waset.org/abstracts/search?q=PESQ" title=" PESQ"> PESQ</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20subtraction" title=" spectral subtraction"> spectral subtraction</a>, <a href="https://publications.waset.org/abstracts/search?q=temporal%20splitting" title=" temporal splitting"> temporal splitting</a>, <a href="https://publications.waset.org/abstracts/search?q=wiener%20filter" title=" wiener filter"> wiener filter</a> </p> <a href="https://publications.waset.org/abstracts/94278/effect-of-noise-reduction-algorithms-on-temporal-splitting-of-speech-signal-to-improve-speech-perception-for-binaural-hearing-aids" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/94278.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">331</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7224</span> Status of Communication and Swallowing Therapy in Patient with a Tracheostomy</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ya-Hui%20Wang">Ya-Hui Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Lower speech therapy rate of tracheostomized patient was noted in comparison with previous researches. This study is aim to shed light on the referral status of speech therapy in those patients in Taiwan. This study developed an analysis for the size and key characteristics of the population of tracheostomized in-patient in the Taiwan. Method: We analyzed National Healthcare Insurance data (The Collaboration Center of Health Information Application, CCHIA) from Jan 1 2010 to Dec 31 2010. Result: over ages 3, number of tracheostomized in-patient is directly proportional to age. A high service loading was observed in North region in comparison with other regions. Only 4.87% of the tracheostomized in-patients were referred for speech therapy, and 1.9% for swallow examination, 2.5% for communication evaluation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=refer" title="refer">refer</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20therapy" title=" speech therapy"> speech therapy</a>, <a href="https://publications.waset.org/abstracts/search?q=training" title=" training"> training</a>, <a href="https://publications.waset.org/abstracts/search?q=rehabilitation" title=" rehabilitation"> rehabilitation</a> </p> <a href="https://publications.waset.org/abstracts/13231/status-of-communication-and-swallowing-therapy-in-patient-with-a-tracheostomy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13231.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">445</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7223</span> Excitation Modeling for Hidden Markov Model-Based Speech Synthesis Based on Wavelet Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Kiran%20Reddy">M. Kiran Reddy</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Sreenivasa%20Rao"> K. Sreenivasa Rao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The conventional Hidden Markov Model (HMM)-based speech synthesis system (HTS) uses only a pulse excitation model, which significantly differs from natural excitation signal. Hence, buzziness can be perceived in the speech generated using HTS. This paper proposes an efficient excitation modeling method that can significantly reduce the buzziness, and improve the quality of HMM-based speech synthesis. The proposed approach models the pitch-synchronous residual frames extracted from the residual excitation signal. Each pitch synchronous residual frame is parameterized using 30 wavelet coefficients. These 30 wavelet coefficients are found to accurately capture the perceptually important information present in the residual waveform. In synthesis phase, the residual frames are reconstructed from the generated wavelet coefficients and are pitch-synchronously overlap-added to generate the excitation signal. The proposed excitation modeling method is integrated into HMM-based speech synthesis system. Evaluation results indicate that the speech synthesized by the proposed excitation model is significantly better than the speech generated using state-of-the-art excitation modeling methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=excitation%20modeling" title="excitation modeling">excitation modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=hidden%20Markov%20models" title=" hidden Markov models"> hidden Markov models</a>, <a href="https://publications.waset.org/abstracts/search?q=pitch-synchronous%20frames" title=" pitch-synchronous frames"> pitch-synchronous frames</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20synthesis" title=" speech synthesis"> speech synthesis</a>, <a href="https://publications.waset.org/abstracts/search?q=wavelet%20coefficients" title=" wavelet coefficients"> wavelet coefficients</a> </p> <a href="https://publications.waset.org/abstracts/102457/excitation-modeling-for-hidden-markov-model-based-speech-synthesis-based-on-wavelet-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/102457.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">252</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7222</span> Speech and Swallowing Function after Tonsillo-Lingual Sulcus Resection with PMMC Flap Reconstruction: A Case Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=K.%20Rhea%20Devaiah">K. Rhea Devaiah</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20S.%20Premalatha"> B. S. Premalatha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Tonsillar Lingual sulcus is the area between the tonsils and the base of the tongue. The surgical resection of the lesions in the head and neck results in changes in speech and swallowing functions. The severity of the speech and swallowing problem depends upon the site and extent of the lesion, types and extent of surgery and also the flexibility of the remaining structures. Need of the study: This paper focuses on the importance of speech and swallowing rehabilitation in an individual with the lesion in the Tonsillar Lingual Sulcus and post-operative functions. Aim: Evaluating the speech and swallow functions post-intensive speech and swallowing rehabilitation. The objectives are to evaluate the speech intelligibility and swallowing functions after intensive therapy and assess the quality of life. Method: The present study describes a report of an individual aged 47years male, with the diagnosis of basaloid squamous cell carcinoma, left tonsillar lingual sulcus (pT2n2M0) and underwent wide local excision with left radical neck dissection with PMMC flap reconstruction. Post-surgery the patient came with a complaint of reduced speech intelligibility, and difficulty in opening the mouth and swallowing. Detailed evaluation of the speech and swallowing functions were carried out such as OPME, articulation test, speech intelligibility, different phases of swallowing and trismus evaluation. Self-reported questionnaires such as SHI-E(Speech handicap Index- Indian English), DHI (Dysphagia handicap Index) and SESEQ -K (Self Evaluation of Swallowing Efficiency in Kannada) were also administered to know what the patient feels about his problem. Based on the evaluation, the patient was diagnosed with pharyngeal phase dysphagia associated with trismus and reduced speech intelligibility. Intensive speech and swallowing therapy was advised weekly twice for the duration of 1 hour. Results: Totally the patient attended 10 intensive speech and swallowing therapy sessions. Results indicated misarticulation of speech sounds such as lingua-palatal sounds. Mouth opening was restricted to one finger width with difficulty chewing, masticating, and swallowing the bolus. Intervention strategies included Oro motor exercise, Indirect swallowing therapy, usage of a trismus device to facilitate mouth opening, and change in the food consistency to help to swallow. A practice session was held with articulation drills to improve the production of speech sounds and also improve speech intelligibility. Significant changes in articulatory production and speech intelligibility and swallowing abilities were observed. The self-rated quality of life measures such as DHI, SHI and SESE Q-K revealed no speech handicap and near-normal swallowing ability indicating the improved QOL after the intensive speech and swallowing therapy. Conclusion: Speech and swallowing therapy post carcinoma in the tonsillar lingual sulcus is crucial as the tongue plays an important role in both speech and swallowing. The role of Speech-language and swallowing therapists in oral cancer should be highlighted in treating these patients and improving the overall quality of life. With intensive speech-language and swallowing therapy post-surgery for oral cancer, there can be a significant change in the speech outcome and swallowing functions depending on the site and extent of lesions which will thereby improve the individual’s QOL. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=oral%20cancer" title="oral cancer">oral cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20and%20swallowing%20therapy" title=" speech and swallowing therapy"> speech and swallowing therapy</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20intelligibility" title=" speech intelligibility"> speech intelligibility</a>, <a href="https://publications.waset.org/abstracts/search?q=trismus" title=" trismus"> trismus</a>, <a href="https://publications.waset.org/abstracts/search?q=quality%20of%20life" title=" quality of life"> quality of life</a> </p> <a href="https://publications.waset.org/abstracts/152166/speech-and-swallowing-function-after-tonsillo-lingual-sulcus-resection-with-pmmc-flap-reconstruction-a-case-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/152166.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">116</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7221</span> Speech Impact Realization via Manipulative Argumentation Techniques in Modern American Political Discourse</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zarine%20Avetisyan">Zarine Avetisyan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Paper presents the discussion of scholars concerning speech impact, peculiarities of its realization, speech strategies, and techniques. Departing from the viewpoints of many prominent linguists, the paper suggests manipulative argumentation be viewed as a most pervasive speech strategy with a certain set of techniques which are to be found in modern American political discourse. The precedence of their occurrence allows us to regard them as pragmatic patterns of speech impact realization in effective public speaking. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=speech%20impact" title="speech impact">speech impact</a>, <a href="https://publications.waset.org/abstracts/search?q=manipulative%20argumentation" title=" manipulative argumentation"> manipulative argumentation</a>, <a href="https://publications.waset.org/abstracts/search?q=political%20discourse" title=" political discourse"> political discourse</a>, <a href="https://publications.waset.org/abstracts/search?q=technique" title=" technique"> technique</a> </p> <a href="https://publications.waset.org/abstracts/31058/speech-impact-realization-via-manipulative-argumentation-techniques-in-modern-american-political-discourse" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31058.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">516</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7220</span> Speech Enhancement Using Kalman Filter in Communication</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Eng.%20Alaa%20K.%20Satti%20Salih">Eng. Alaa K. Satti Salih</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Revolutions Applications such as telecommunications, hands-free communications, recording, etc. which need at least one microphone, the signal is usually infected by noise and echo. The important application is the speech enhancement, which is done to remove suppressed noises and echoes taken by a microphone, beside preferred speech. Accordingly, the microphone signal has to be cleaned using digital signal processing DSP tools before it is played out, transmitted, or stored. Engineers have so far tried different approaches to improving the speech by get back the desired speech signal from the noisy observations. Especially Mobile communication, so in this paper will do reconstruction of the speech signal, observed in additive background noise, using the Kalman filter technique to estimate the parameters of the Autoregressive Process (AR) in the state space model and the output speech signal obtained by the MATLAB. The accurate estimation by Kalman filter on speech would enhance and reduce the noise then compare and discuss the results between actual values and estimated values which produce the reconstructed signals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=autoregressive%20process" title="autoregressive process">autoregressive process</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=Matlab" title=" Matlab"> Matlab</a>, <a href="https://publications.waset.org/abstracts/search?q=noise%20speech" title=" noise speech"> noise speech</a> </p> <a href="https://publications.waset.org/abstracts/7182/speech-enhancement-using-kalman-filter-in-communication" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7182.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">350</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7219</span> Analysis of Interleaving Scheme for Narrowband VoIP System under Pervasive Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Monica%20Sharma">Monica Sharma</a>, <a href="https://publications.waset.org/abstracts/search?q=Harjit%20Pal%20Singh"> Harjit Pal Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Jasbinder%20Singh"> Jasbinder Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Manju%20Bala"> Manju Bala</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In Voice over Internet Protocol (VoIP) system, the speech signal is degraded when passed through the network layers. The speech signal is processed through the best effort policy based IP network, which leads to the network degradations including delay, packet loss and jitter. The packet loss is the major issue of the degradation in the VoIP signal quality; even a single lost packet may generate audible distortion in the decoded speech signal. In addition to these network degradations, the quality of the speech signal is also affected by the environmental noises and coder distortions. The signal quality of the VoIP system is improved through the interleaving technique. The performance of the system is evaluated for various types of noises at different network conditions. The performance of the enhanced VoIP signal is evaluated using perceptual evaluation of speech quality (PESQ) measurement for narrow band signal. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=VoIP" title="VoIP">VoIP</a>, <a href="https://publications.waset.org/abstracts/search?q=interleaving" title=" interleaving"> interleaving</a>, <a href="https://publications.waset.org/abstracts/search?q=packet%20loss" title=" packet loss"> packet loss</a>, <a href="https://publications.waset.org/abstracts/search?q=packet%20size" title=" packet size"> packet size</a>, <a href="https://publications.waset.org/abstracts/search?q=background%20noise" title=" background noise "> background noise </a> </p> <a href="https://publications.waset.org/abstracts/14305/analysis-of-interleaving-scheme-for-narrowband-voip-system-under-pervasive-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14305.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">486</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7218</span> Freedom of Speech and Involvement in Hatred Speech on Social Media Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sara%20Chinnasamy">Sara Chinnasamy</a>, <a href="https://publications.waset.org/abstracts/search?q=Michelle%20Gun"> Michelle Gun</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Adnan%20Hashim"> M. Adnan Hashim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Federal Constitution guarantees Malaysians the right to free speech and expression; yet hatred speech can be commonly found on social media platforms such as Facebook, Twitter, and Instagram. In Malaysia social media sphere, most hatred speech involves religion, race and politics. Recent cases of racial attacks on social media have created social tensions among Malaysians. Many Malaysians always argue on their rights to freedom of speech. However, there are laws that limit their expression to the public and protecting social media users from being a victim of hate speech. This paper aims to explore the attitude and involvement of Malaysian netizens towards freedom of speech and hatred speech on social media. It also examines the relationship between involvement in hatred speech among Malaysian netizens and attitude towards freedom of speech. For most Malaysians, practicing total freedom of speech in the open is unthinkable. As a result, the best channel to articulate their feelings and opinions liberally is the internet. With the advent of the internet medium, more and more Malaysians are conveying their viewpoints using the various internet channels although sensitivity of the audience is seldom taken into account. Consequently, this situation has led to pockets of social disharmony among the citizens. Although this unhealthy activity is denounced by the authority, netizens are generally of the view that they have the right to write anything they want. Using the quantitative method, survey was conducted among Malaysians aged between 18 and 50 years who are active social media users. Results from the survey reveal that despite a weak relationship level between hatred speech involvement on social media and attitude towards freedom of speech, the association is still considerably significant. As such, it can be safely presumed that hatred speech on social media occurs due to the freedom of speech that exists by way of social media channels. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=freedom%20of%20speech" title="freedom of speech">freedom of speech</a>, <a href="https://publications.waset.org/abstracts/search?q=hatred%20speech" title=" hatred speech"> hatred speech</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20media" title=" social media"> social media</a>, <a href="https://publications.waset.org/abstracts/search?q=Malaysia" title=" Malaysia"> Malaysia</a>, <a href="https://publications.waset.org/abstracts/search?q=netizens" title=" netizens"> netizens</a> </p> <a href="https://publications.waset.org/abstracts/72863/freedom-of-speech-and-involvement-in-hatred-speech-on-social-media-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72863.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">462</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7217</span> Possibilities, Challenges and the State of the Art of Automatic Speech Recognition in Air Traffic Control</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Van%20Nhan%20Nguyen">Van Nhan Nguyen</a>, <a href="https://publications.waset.org/abstracts/search?q=Harald%20Holone"> Harald Holone</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Over the past few years, a lot of research has been conducted to bring Automatic Speech Recognition (ASR) into various areas of Air Trafﬁc Control (ATC), such as air trafﬁc control simulation and training, monitoring live operators for with the aim of safety improvements, air trafﬁc controller workload measurement and conducting analysis on large quantities controller-pilot speech. Due to the high accuracy requirements of the ATC context and its unique challenges, automatic speech recognition has not been widely adopted in this ﬁeld. With the aim of providing a good starting point for researchers who are interested bringing automatic speech recognition into ATC, this paper gives an overview of possibilities and challenges of applying automatic speech recognition in air trafﬁc control. To provide this overview, we present an updated literature review of speech recognition technologies in general, as well as speciﬁc approaches relevant to the ATC context. Based on this literature review, criteria for selecting speech recognition approaches for the ATC domain are presented, and remaining challenges and possible solutions are discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=automatic%20speech%20recognition" title="automatic speech recognition">automatic speech recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=asr" title=" asr"> asr</a>, <a href="https://publications.waset.org/abstracts/search?q=air%20traffic%20control" title=" air traffic control"> air traffic control</a>, <a href="https://publications.waset.org/abstracts/search?q=atc" title=" atc"> atc</a> </p> <a href="https://publications.waset.org/abstracts/31004/possibilities-challenges-and-the-state-of-the-art-of-automatic-speech-recognition-in-air-traffic-control" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31004.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">409</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7216</span> Minimum Data of a Speech Signal as Special Indicators of Identification in Phonoscopy</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nazaket%20Gazieva">Nazaket Gazieva</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Voice biometric data associated with physiological, psychological and other factors are widely used in forensic phonoscopy. There are various methods for identifying and verifying a person by voice. This article explores the minimum speech signal data as individual parameters of a speech signal. Monozygotic twins are believed to be genetically identical. Using the minimum data of the speech signal, we came to the conclusion that the voice imprint of monozygotic twins is individual. According to the conclusion of the experiment, we can conclude that the minimum indicators of the speech signal are more stable and reliable for phonoscopic examinations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=phonogram" title="phonogram">phonogram</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20signal" title=" speech signal"> speech signal</a>, <a href="https://publications.waset.org/abstracts/search?q=temporal%20characteristics" title=" temporal characteristics"> temporal characteristics</a>, <a href="https://publications.waset.org/abstracts/search?q=fundamental%20frequency" title=" fundamental frequency"> fundamental frequency</a>, <a href="https://publications.waset.org/abstracts/search?q=biometric%20fingerprints" title=" biometric fingerprints"> biometric fingerprints</a> </p> <a href="https://publications.waset.org/abstracts/110332/minimum-data-of-a-speech-signal-as-special-indicators-of-identification-in-phonoscopy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/110332.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">147</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7215</span> Intervention of Self-Limiting L1 Inner Speech during L2 Presentations: A Study of Bangla-English Bilinguals</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdul%20Wahid">Abdul Wahid</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Inner speech, also known as verbal thinking, self-talk or private speech, is characterized by the subjective language experience in the absence of overt or audible speech. It is a psychological form of verbal activity which is being rehearsed without the articulation of any sound wave. In Psychology, self-limiting speech means the type of speech which contains information that inhibits the development of the self. People, in most cases, experience inner speech in their first language. It is very frequent in Bangladesh where the Bangla (L1) speaking students lose track of speech during their presentations in English (L2). This paper investigates into the long pauses (more than 0.4 seconds long) in English (L2) presentations by Bangla speaking students (18-21 year old) and finds the intervention of Bangla (L1) inner speech as one of its causes. The overt speeches of the presenters are placed on Audacity Audio Editing software where the length of pauses are measured in milliseconds. Varieties of inner speech questionnaire (VISQ) have been conducted randomly amongst the participants out of whom 20 were selected who have similar phenomenology of inner speech. They have been interviewed to describe the type and content of the voices that went on in their head during the long pauses. The qualitative interview data are then codified and converted into quantitative data. It was observed that in more than 80% cases students experience self-limiting inner speech/self-talk during their unwanted pauses in L2 presentations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bangla-English%20Bilinguals" title="Bangla-English Bilinguals">Bangla-English Bilinguals</a>, <a href="https://publications.waset.org/abstracts/search?q=inner%20speech" title=" inner speech"> inner speech</a>, <a href="https://publications.waset.org/abstracts/search?q=L1%20intervention%20in%20bilingualism" title=" L1 intervention in bilingualism"> L1 intervention in bilingualism</a>, <a href="https://publications.waset.org/abstracts/search?q=motor%20schema" title=" motor schema"> motor schema</a>, <a href="https://publications.waset.org/abstracts/search?q=pauses" title=" pauses"> pauses</a>, <a href="https://publications.waset.org/abstracts/search?q=phonological%20loop" title=" phonological loop"> phonological loop</a>, <a href="https://publications.waset.org/abstracts/search?q=phonological%20store" title=" phonological store"> phonological store</a>, <a href="https://publications.waset.org/abstracts/search?q=working%20memory" title=" working memory"> working memory</a> </p> <a href="https://publications.waset.org/abstracts/128980/intervention-of-self-limiting-l1-inner-speech-during-l2-presentations-a-study-of-bangla-english-bilinguals" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/128980.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">157</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7214</span> Automatic Segmentation of the Clean Speech Signal</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20A.%20Ben%20Messaoud">M. A. Ben Messaoud</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Bouzid"> A. Bouzid</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Ellouze"> N. Ellouze</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Speech Segmentation is the measure of the change point detection for partitioning an input speech signal into regions each of which accords to only one speaker. In this paper, we apply two features based on multi-scale product (MP) of the clean speech, namely the spectral centroid of MP, and the zero crossings rate of MP. We focus on multi-scale product analysis as an important tool for segmentation extraction. The multi-scale product is based on making the product of the speech wavelet transform coefficients at three successive dyadic scales. We have evaluated our method on the Keele database. Experimental results show the effectiveness of our method presenting a good performance. It shows that the two simple features can find word boundaries, and extracted the segments of the clean speech. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multiscale%20product" title="multiscale product">multiscale product</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20centroid" title=" spectral centroid"> spectral centroid</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20segmentation" title=" speech segmentation"> speech segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=zero%20crossings%20rate" title=" zero crossings rate"> zero crossings rate</a> </p> <a href="https://publications.waset.org/abstracts/17566/automatic-segmentation-of-the-clean-speech-signal" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17566.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">504</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7213</span> The Capacity of Mel Frequency Cepstral Coefficients for Speech Recognition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fawaz%20S.%20Al-Anzi">Fawaz S. Al-Anzi</a>, <a href="https://publications.waset.org/abstracts/search?q=Dia%20AbuZeina"> Dia AbuZeina</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=speech%20recognition" title="speech recognition">speech recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=acoustic%20features" title=" acoustic features"> acoustic features</a>, <a href="https://publications.waset.org/abstracts/search?q=mel%20frequency" title=" mel frequency"> mel frequency</a>, <a href="https://publications.waset.org/abstracts/search?q=cepstral%20coefficients" title=" cepstral coefficients"> cepstral coefficients</a> </p> <a href="https://publications.waset.org/abstracts/78382/the-capacity-of-mel-frequency-cepstral-coefficients-for-speech-recognition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78382.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">265</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7212</span> Eisenhower’s Farewell Speech: Initial and Continuing Communication Effects</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=B.%20Kuiper">B. Kuiper</a> </p> <p class="card-text"><strong>Abstract:</strong></p> When Dwight D. Eisenhower delivered his final Presidential speech in 1961, he was using the opportunity to bid farewell to America, but he was also trying to warn his fellow countrymen about deeper challenges threatening the country. In this analysis, Eisenhower’s speech is examined in light of the impact it had on American culture, communication concepts, and political ramifications. The paper initially highlights the previous literature on the speech, especially in light of its 50<sup>th </sup>anniversary, and reveals a man whose main concern was how the speech’s words would affect his beloved country. The painstaking approach to the wording of the speech to reveal the intent is key, particularly in light of analyzing the motivations according to “virtuous communication.” This philosophical construct indicates that Eisenhower’s Farewell Address was crafted carefully according to a departing President’s deepest values and concerns, concepts that he wanted to pass along to his successor, to his country, and even to the world. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Eisenhower" title="Eisenhower">Eisenhower</a>, <a href="https://publications.waset.org/abstracts/search?q=mass%20communication" title=" mass communication"> mass communication</a>, <a href="https://publications.waset.org/abstracts/search?q=political%20speech" title=" political speech"> political speech</a>, <a href="https://publications.waset.org/abstracts/search?q=rhetoric" title=" rhetoric"> rhetoric</a> </p> <a href="https://publications.waset.org/abstracts/50004/eisenhowers-farewell-speech-initial-and-continuing-communication-effects" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50004.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">277</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7211</span> A Sparse Representation Speech Denoising Method Based on Adapted Stopping Residue Error</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Qianhua%20He">Qianhua He</a>, <a href="https://publications.waset.org/abstracts/search?q=Weili%20Zhou"> Weili Zhou</a>, <a href="https://publications.waset.org/abstracts/search?q=Aiwu%20Chen"> Aiwu Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A sparse representation speech denoising method based on adapted stopping residue error was presented in this paper. Firstly, the cross-correlation between the clean speech spectrum and the noise spectrum was analyzed, and an estimation method was proposed. In the denoising method, an over-complete dictionary of the clean speech power spectrum was learned with the K-singular value decomposition (K-SVD) algorithm. In the sparse representation stage, the stopping residue error was adaptively achieved according to the estimated cross-correlation and the adjusted noise spectrum, and the orthogonal matching pursuit (OMP) approach was applied to reconstruct the clean speech spectrum from the noisy speech. Finally, the clean speech was re-synthesised via the inverse Fourier transform with the reconstructed speech spectrum and the noisy speech phase. The experiment results show that the proposed method outperforms the conventional methods in terms of subjective and objective measure. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=speech%20denoising" title="speech denoising">speech denoising</a>, <a href="https://publications.waset.org/abstracts/search?q=sparse%20representation" title=" sparse representation"> sparse representation</a>, <a href="https://publications.waset.org/abstracts/search?q=k-singular%20value%20decomposition" title=" k-singular value decomposition"> k-singular value decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=orthogonal%20matching%20pursuit" title=" orthogonal matching pursuit"> orthogonal matching pursuit</a> </p> <a href="https://publications.waset.org/abstracts/66670/a-sparse-representation-speech-denoising-method-based-on-adapted-stopping-residue-error" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66670.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">502</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7210</span> Features of Normative and Pathological Realizations of Sibilant Sounds for Computer-Aided Pronunciation Evaluation in Children</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zuzanna%20Miodonska">Zuzanna Miodonska</a>, <a href="https://publications.waset.org/abstracts/search?q=Michal%20Krecichwost"> Michal Krecichwost</a>, <a href="https://publications.waset.org/abstracts/search?q=Pawel%20Badura"> Pawel Badura</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Sigmatism (lisping) is a speech disorder in which sibilant consonants are mispronounced. The diagnosis of this phenomenon is usually based on the auditory assessment. However, the progress in speech analysis techniques creates a possibility of developing computer-aided sigmatism diagnosis tools. The aim of the study is to statistically verify whether specific acoustic features of sibilant sounds may be related to pronunciation correctness. Such knowledge can be of great importance while implementing classifiers and designing novel tools for automatic sibilants pronunciation evaluation. The study covers analysis of various speech signal measures, including features proposed in the literature for the description of normative sibilants realization. Amplitudes and frequencies of three fricative formants (FF) are extracted based on local spectral maxima of the friction noise. Skewness, kurtosis, four normalized spectral moments (SM) and 13 mel-frequency cepstral coefficients (MFCC) with their 1st and 2nd derivatives (13 Delta and 13 Delta-Delta MFCC) are included in the analysis as well. The resulting feature vector contains 51 measures. The experiments are performed on the speech corpus containing words with selected sibilant sounds (/ʃ, ʒ/) pronounced by 60 preschool children with proper pronunciation or with natural pathologies. In total, 224 /ʃ/ segments and 191 /ʒ/ segments are employed in the study. The Mann-Whitney U test is employed for the analysis of stigmatism and normative pronunciation. Statistically, significant differences are obtained in most of the proposed features in children divided into these two groups at p < 0.05. All spectral moments and fricative formants appear to be distinctive between pathology and proper pronunciation. These metrics describe the friction noise characteristic for sibilants, which makes them particularly promising for the use in sibilants evaluation tools. Correspondences found between phoneme feature values and an expert evaluation of the pronunciation correctness encourage to involve speech analysis tools in diagnosis and therapy of sigmatism. Proposed feature extraction methods could be used in a computer-assisted stigmatism diagnosis or therapy systems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computer-aided%20pronunciation%20evaluation" title="computer-aided pronunciation evaluation">computer-aided pronunciation evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=sigmatism%20diagnosis" title=" sigmatism diagnosis"> sigmatism diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20signal%20analysis" title=" speech signal analysis"> speech signal analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20verification" title=" statistical verification"> statistical verification</a> </p> <a href="https://publications.waset.org/abstracts/65569/features-of-normative-and-pathological-realizations-of-sibilant-sounds-for-computer-aided-pronunciation-evaluation-in-children" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65569.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">305</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=non-Intrusive%20speech%20evaluation&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=non-Intrusive%20speech%20evaluation&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=non-Intrusive%20speech%20evaluation&page=4">4</a></li> <li class="page-item"><a class="page-link" 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