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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">7807</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">7806</span> Advances in Artificial intelligence Using Speech Recognition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Khaled%20M.%20Alhawiti">Khaled M. Alhawiti</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition. <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%20phonetic" title=" acoustic phonetic"> acoustic phonetic</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title=" artificial intelligence"> artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=hidden%20markov%20models%20%28HMM%29" title=" hidden markov models (HMM)"> hidden markov models (HMM)</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20models%20of%20speech%20recognition" title=" statistical models of speech recognition"> statistical models of speech recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=human%20machine%20performance" title=" human machine performance"> human machine performance</a> </p> <a href="https://publications.waset.org/abstracts/26319/advances-in-artificial-intelligence-using-speech-recognition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/26319.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">481</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">7805</span> Speech Intelligibility Improvement Using Variable Level Decomposition DWT</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Samba%20Raju">Samba Raju</a>, <a href="https://publications.waset.org/abstracts/search?q=Chiluveru"> Chiluveru</a>, <a href="https://publications.waset.org/abstracts/search?q=Manoj%20Tripathy"> Manoj Tripathy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Intelligibility is an essential characteristic of a speech signal, which is used to help in the understanding of information in speech signal. Background noise in the environment can deteriorate the intelligibility of a recorded speech. In this paper, we presented a simple variance subtracted - variable level discrete wavelet transform, which improve the intelligibility of speech. The proposed algorithm does not require an explicit estimation of noise, i.e., prior knowledge of the noise; hence, it is easy to implement, and it reduces the computational burden. The proposed algorithm decides a separate decomposition level for each frame based on signal dominant and dominant noise criteria. The performance of the proposed algorithm is evaluated with speech intelligibility measure (STOI), and results obtained are compared with Universal Discrete Wavelet Transform (DWT) thresholding and Minimum Mean Square Error (MMSE) methods. The experimental results revealed that the proposed scheme outperformed competing methods <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=discrete%20wavelet%20transform" title="discrete wavelet transform">discrete wavelet transform</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=STOI" title=" STOI"> STOI</a>, <a href="https://publications.waset.org/abstracts/search?q=standard%20deviation" title=" standard deviation"> standard deviation</a> </p> <a href="https://publications.waset.org/abstracts/115620/speech-intelligibility-improvement-using-variable-level-decomposition-dwt" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/115620.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">154</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">7804</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">7803</span> The Speech Acts of Selected Classroom Encounters: Analyzing the Speech Acts of a Career Technology Lesson</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Michael%20Amankwaa%20Adu">Michael Amankwaa Adu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study investigates the speech acts employed by a Career Technology teacher during classroom interactions in a junior high school. While much research exists on speech acts in language teaching, little attention has been given to technical subjects. This has created a gap in understanding how teachers of non-language subjects utilize speech acts in classroom communication. This study aims to analyze the types and frequencies of speech acts used by a Career Technology teacher during three key classroom encounters: lesson introduction, content delivery, and classroom management. Using a mixed-methods approach, the study examines 113 utterances from the teacher's lesson, categorizing them into four primary speech act types: directives, assertives, expressives, and commissives. Directives emerged as the most dominant form, accounting for 59.3% of the utterances, followed by assertives (20.4%), expressives (14.2%), and commissives (6.2%). No declarations were observed. The study demonstrates how the teacher uses directives to manage student behavior and assertives to reinforce information. Expressives are used sparingly but play a role in motivating or disciplining students, while commissives help establish classroom rules and set expectations. The findings contribute to understanding classroom interaction strategies in non-language subjects, offering insights that could inform teacher training and curriculum development. The study underscores the importance of effective communication in technical subjects and suggests ways in which language teaching techniques might be integrated into other subject areas. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=classroom%20management" title="classroom management">classroom management</a>, <a href="https://publications.waset.org/abstracts/search?q=directives" title=" directives"> directives</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20acts" title=" speech acts"> speech acts</a>, <a href="https://publications.waset.org/abstracts/search?q=technical%20subjects." title=" technical subjects."> technical subjects.</a>, <a href="https://publications.waset.org/abstracts/search?q=assertives" title=" assertives"> assertives</a> </p> <a href="https://publications.waset.org/abstracts/191495/the-speech-acts-of-selected-classroom-encounters-analyzing-the-speech-acts-of-a-career-technology-lesson" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/191495.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">28</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">7802</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">7801</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">7800</span> Influence of Loudness Compression on Hearing with Bone Anchored Hearing Implants</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Anja%20Kurz">Anja Kurz</a>, <a href="https://publications.waset.org/abstracts/search?q=Marc%20Flynn"> Marc Flynn</a>, <a href="https://publications.waset.org/abstracts/search?q=Tobias%20Good"> Tobias Good</a>, <a href="https://publications.waset.org/abstracts/search?q=Marco%20Caversaccio"> Marco Caversaccio</a>, <a href="https://publications.waset.org/abstracts/search?q=Martin%20Kompis"> Martin Kompis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Bone Anchored Hearing Implants (BAHI) are routinely used in patients with conductive or mixed hearing loss, e.g. if conventional air conduction hearing aids cannot be used. New sound processors and new fitting software now allow the adjustment of parameters such as loudness compression ratios or maximum power output separately. Today it is unclear, how the choice of these parameters influences aided speech understanding in BAHI users. In this prospective experimental study, the effect of varying the compression ratio and lowering the maximum power output in a BAHI were investigated. Twelve experienced adult subjects with a mixed hearing loss participated in this study. Four different compression ratios (1.0; 1.3; 1.6; 2.0) were tested along with two different maximum power output settings, resulting in a total of eight different programs. Each participant tested each program during two weeks. A blinded Latin square design was used to minimize bias. For each of the eight programs, speech understanding in quiet and in noise was assessed. For speech in quiet, the Freiburg number test and the Freiburg monosyllabic word test at 50, 65, and 80 dB SPL were used. For speech in noise, the Oldenburg sentence test was administered. Speech understanding in quiet and in noise was improved significantly in the aided condition in any program, when compared to the unaided condition. However, no significant differences were found between any of the eight programs. In contrast, on a subjective level there was a significant preference for medium compression ratios of 1.3 to 1.6 and higher maximum power output. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bone%20Anchored%20Hearing%20Implant" title="Bone Anchored Hearing Implant">Bone Anchored Hearing Implant</a>, <a href="https://publications.waset.org/abstracts/search?q=baha" title=" baha"> baha</a>, <a href="https://publications.waset.org/abstracts/search?q=compression" title=" compression"> compression</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum%20power%20output" title=" maximum power output"> maximum power output</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20understanding" title=" speech understanding"> speech understanding</a> </p> <a href="https://publications.waset.org/abstracts/2657/influence-of-loudness-compression-on-hearing-with-bone-anchored-hearing-implants" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2657.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">393</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">7799</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">7798</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">7797</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">7796</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">7795</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">7794</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">7793</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">7792</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">7791</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">7790</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">7789</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">158</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">7788</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">7787</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">7786</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">7785</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">7784</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">7783</span> Childhood Apraxia of Speech and Autism: Interaction Influences and Treatment </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Elad%20Vashdi">Elad Vashdi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> It is common to find speech deficit among children diagnosed with Autism. It can be found in the clinical field and recently in research. One of the DSM-V criteria suggests a speech delay (Delay in, or total lack of, the development of spoken language), but doesn't explain the cause of it. A common perception among professionals and families is that the inability to talk results from the autism. Autism is a name for a syndrome which just describes a phenomenon and is defined behaviorally. Since it is not based yet on a physiological gold standard, one can not conclude the nature of a deficit based on the name of the syndrome. A wide retrospective research (n=270) which included children with motor speech difficulties was conducted in Israel. The study analyzed entry evaluations in a private clinic during the years 2006-2013. The data was extracted from the reports. High percentage of children diagnosed with Autism (60%) was found. This result demonstrates the high relationship between Autism and motor speech problem. It also supports recent findings in research of Childhood apraxia of speech (CAS) occurrence among children with ASD. Only small percentage of the participants in this research (10%) were diagnosed with CAS even though their verbal deficits well fitted the guidelines for CAS diagnosis set by ASHA in 2007. This fact raises questions regarding the diagnostic procedure in Israel. The understanding that CAS might highly exist within Autism and can have a remarkable influence on the course of early development should be a guiding tool within the diagnosis procedure. CAS can explain the nature of the speech problem among some of the autistic children and guide the treatment in a more accurate way. Calculating the prevalence of CAS which includes the comorbidity with ASD reveals new numbers and suggests treating differently the CAS population. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=childhood%20apraxia%20of%20speech" title="childhood apraxia of speech">childhood apraxia of speech</a>, <a href="https://publications.waset.org/abstracts/search?q=Autism" title=" Autism"> Autism</a>, <a href="https://publications.waset.org/abstracts/search?q=treatment" title=" treatment"> treatment</a>, <a href="https://publications.waset.org/abstracts/search?q=speech" title=" speech"> speech</a> </p> <a href="https://publications.waset.org/abstracts/56050/childhood-apraxia-of-speech-and-autism-interaction-influences-and-treatment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/56050.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">7782</span> Speech Acts and Politeness Strategies in an EFL Classroom in Georgia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tinatin%20Kurdghelashvili">Tinatin Kurdghelashvili</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper deals with the usage of speech acts and politeness strategies in an EFL classroom in Georgia (Rep of). It explores the students’ and the teachers’ practice of the politeness strategies and the speech acts of apology, thanking, request, compliment/encouragement, command, agreeing/disagreeing, addressing and code switching. The research method includes observation as well as a questionnaire. The target group involves the students from Georgian public schools and two certified, experienced local English teachers. The analysis is based on Searle’s Speech Act Theory and Brown and Levinson’s politeness strategies. The findings show that the students have certain knowledge regarding politeness yet they fail to apply them in English communication. In addition, most of the speech acts from the classroom interaction are used by the teachers and not the students. Thereby, it is suggested that teachers should cultivate the students’ communicative competence and attempt to give them opportunities to practice more English speech acts than they do today. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=english%20as%20a%20foreign%20language" title="english as a foreign language">english as a foreign language</a>, <a href="https://publications.waset.org/abstracts/search?q=Georgia" title=" Georgia"> Georgia</a>, <a href="https://publications.waset.org/abstracts/search?q=politeness%20principles" title=" politeness principles"> politeness principles</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20acts" title=" speech acts"> speech acts</a> </p> <a href="https://publications.waset.org/abstracts/17320/speech-acts-and-politeness-strategies-in-an-efl-classroom-in-georgia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17320.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">647</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">7781</span> Speech Detection Model Based on Deep Neural Networks Classifier for Speech Emotions Recognition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Shoiynbek">A. Shoiynbek</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Kozhakhmet"> K. Kozhakhmet</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Menezes"> P. Menezes</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20Kuanyshbay"> D. Kuanyshbay</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20Bayazitov"> D. Bayazitov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=deep%20neural%20networks" title="deep neural networks">deep neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20detection" title=" speech detection"> speech detection</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20emotion%20recognition" title=" speech emotion recognition"> speech emotion recognition</a>, <a href="https://publications.waset.org/abstracts/search?q=Mel-frequency%20cepstrum%20coefficients" title=" Mel-frequency cepstrum coefficients"> Mel-frequency cepstrum coefficients</a>, <a href="https://publications.waset.org/abstracts/search?q=collecting%20speech%20emotion%20corpus" title=" collecting speech emotion corpus"> collecting speech emotion corpus</a>, <a href="https://publications.waset.org/abstracts/search?q=collecting%20speech%20emotion%20dataset" title=" collecting speech emotion dataset"> collecting speech emotion dataset</a>, <a href="https://publications.waset.org/abstracts/search?q=Kazakh%20speech%20dataset" title=" Kazakh speech dataset"> Kazakh speech dataset</a> </p> <a href="https://publications.waset.org/abstracts/152814/speech-detection-model-based-on-deep-neural-networks-classifier-for-speech-emotions-recognition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/152814.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">106</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">7780</span> The Effect of The Speaker's Speaking Style as A Factor of Understanding and Comfort of The Listener</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Made%20Rahayu%20Putri%20Saron">Made Rahayu Putri Saron</a>, <a href="https://publications.waset.org/abstracts/search?q=Mochamad%20Nizar%20Palefi%20Ma%E2%80%99ady"> Mochamad Nizar Palefi Ma’ady</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Communication skills are important in everyday life, communication can be done verbally in the form of oral or written and nonverbal in the form of expressions or body movements. Good communication should be able to provide information clearly, and there is feedback from the speaker and listener. However, it is often found that the information conveyed is not clear, and there is no feedback from the listeners, so it cannot be ensured that the communication is effective and understandable. The speaker's understanding of the topic is one of the supporting factors for the listener to be able to accept the meaning of the conversation. However, based on the results of the literature review, it found that the influence factors of person speaking style are as follows: (i) environmental conditions; (ii) voice, articulation, and accent; (iii) gender; (iv) personality; (v) speech disorders (Dysarthria); when speaking also have an important influence on speaker’s speaking style. It can be concluded the factors that support understanding and comfort of the listener are dependent on the nature of the speaker (environmental conditions, voice, gender, personality) or also it the speaker have speech disorders. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=listener" title="listener">listener</a>, <a href="https://publications.waset.org/abstracts/search?q=public%20speaking" title=" public speaking"> public speaking</a>, <a href="https://publications.waset.org/abstracts/search?q=speaking%20style" title=" speaking style"> speaking style</a>, <a href="https://publications.waset.org/abstracts/search?q=understanding" title=" understanding"> understanding</a>, <a href="https://publications.waset.org/abstracts/search?q=and%20comfortable%20factor" title=" and comfortable factor"> and comfortable factor</a> </p> <a href="https://publications.waset.org/abstracts/145442/the-effect-of-the-speakers-speaking-style-as-a-factor-of-understanding-and-comfort-of-the-listener" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145442.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">176</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">7779</span> The Influence of Advertising Captions on the Internet through the Consumer Purchasing Decision</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Suwimol%20Apapol">Suwimol Apapol</a>, <a href="https://publications.waset.org/abstracts/search?q=Punrapha%20Praditpong"> Punrapha Praditpong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The objectives of the study were to find out the frequencies of figures of speech in fragrance advertising captions as well as 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 several Goods service. 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 which is in harmony with the research hypotheses as well. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=advertising%20captions" title="advertising captions">advertising captions</a>, <a href="https://publications.waset.org/abstracts/search?q=captions%20on%20internet" title=" captions on internet"> captions on internet</a>, <a href="https://publications.waset.org/abstracts/search?q=consumer%20purchasing%20decision" title=" consumer purchasing decision"> consumer purchasing decision</a>, <a href="https://publications.waset.org/abstracts/search?q=e-commerce" title=" e-commerce"> e-commerce</a> </p> <a href="https://publications.waset.org/abstracts/39966/the-influence-of-advertising-captions-on-the-internet-through-the-consumer-purchasing-decision" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39966.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">274</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=speech%20understanding&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=speech%20understanding&page=3">3</a></li> <li class="page-item"><a class="page-link" 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