Search results for: S. Haghipour

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Haghipour</title> <meta name="description" content="Search results for: S. Haghipour"> <meta name="keywords" content="S. Haghipour"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" type="button" data-toggle="collapse" data-target="#navbarMenu" aria-controls="navbarMenu" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-icon"></span> </button> <div class="w-100"> <div class="d-none d-lg-flex flex-row-reverse"> <form method="get" action="https://waset.org/search" class="form-inline my-2 my-lg-0"> <input class="form-control mr-sm-2" type="search" placeholder="Search Conferences" value="S. 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Haghipour"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 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> 2</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: S. Haghipour</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> Using New Machine Algorithms to Classify Iranian Musical Instruments According to Temporal, Spectral and Coefficient Features</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ronak%20Khosravi">Ronak Khosravi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahmood%20Abbasi%20Layegh"> Mahmood Abbasi Layegh</a>, <a href="https://publications.waset.org/abstracts/search?q=Siamak%20Haghipour"> Siamak Haghipour</a>, <a href="https://publications.waset.org/abstracts/search?q=Avin%20Esmaili"> Avin Esmaili</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a study on classification of musical woodwind instruments using a small set of features selected from a broad range of extracted ones by the sequential forward selection method was carried out. Firstly, we extract 42 features for each record in the music database of 402 sound files belonging to five different groups of Flutes (end blown and internal duct), Single –reed, Double –reed (exposed and capped), Triple reed and Quadruple reed. Then, the sequential forward selection method is adopted to choose the best feature set in order to achieve very high classification accuracy. Two different classification techniques of support vector machines and relevance vector machines have been tested out and an accuracy of up to 96% can be achieved by using 21 time, frequency and coefficient features and relevance vector machine with the Gaussian kernel function. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=coefficient%20features" title="coefficient features">coefficient features</a>, <a href="https://publications.waset.org/abstracts/search?q=relevance%20vector%20machines" title=" relevance vector machines"> relevance vector machines</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20features" title=" spectral features"> spectral features</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machines" title=" support vector machines"> support vector machines</a>, <a href="https://publications.waset.org/abstracts/search?q=temporal%20features" title=" temporal features"> temporal features</a> </p> <a href="https://publications.waset.org/abstracts/54321/using-new-machine-algorithms-to-classify-iranian-musical-instruments-according-to-temporal-spectral-and-coefficient-features" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54321.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">1</span> The Optimum Mel-Frequency Cepstral Coefficients (MFCCs) Contribution to Iranian Traditional Music Genre Classification by Instrumental Features</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Abbasi%20Layegh">M. Abbasi Layegh</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Haghipour"> S. Haghipour</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Athari"> K. Athari</a>, <a href="https://publications.waset.org/abstracts/search?q=R.%20Khosravi"> R. Khosravi</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Tafkikialamdari"> M. Tafkikialamdari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An approach to find the optimum mel-frequency cepstral coefficients (MFCCs) for the Radif of Mirzâ Ábdollâh, which is the principal emblem and the heart of Persian music, performed by most famous Iranian masters on two Iranian stringed instruments ‘Tar’ and ‘Setar’ is proposed. While investigating the variance of MFCC for each record in themusic database of 1500 gushe of the repertoire belonging to 12 modal systems (dastgâh and âvâz), we have applied the Fuzzy C-Mean clustering algorithm on each of the 12 coefficient and different combinations of those coefficients. We have applied the same experiment while increasing the number of coefficients but the clustering accuracy remained the same. Therefore, we can conclude that the first 7 MFCCs (V-7MFCC) are enough for classification of The Radif of Mirzâ Ábdollâh. Classical machine learning algorithms such as MLP neural networks, K-Nearest Neighbors (KNN), Gaussian Mixture Model (GMM), Hidden Markov Model (HMM) and Support Vector Machine (SVM) have been employed. Finally, it can be realized that SVM shows a better performance in this study. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=radif%20of%20Mirz%C3%A2%20%C3%81bdoll%C3%A2h" title="radif of Mirzâ Ábdollâh">radif of Mirzâ Ábdollâh</a>, <a href="https://publications.waset.org/abstracts/search?q=Gushe" title=" Gushe"> Gushe</a>, <a href="https://publications.waset.org/abstracts/search?q=mel%20frequency%20cepstral%20coefficients" title=" mel frequency cepstral coefficients"> mel frequency cepstral coefficients</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20c-mean%20clustering%20algorithm" title=" fuzzy c-mean clustering algorithm"> fuzzy c-mean clustering algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=k-nearest%20neighbors%20%28KNN%29" title=" k-nearest neighbors (KNN)"> k-nearest neighbors (KNN)</a>, <a href="https://publications.waset.org/abstracts/search?q=gaussian%20mixture%20model%20%28GMM%29" title=" gaussian mixture model (GMM)"> gaussian mixture model (GMM)</a>, <a href="https://publications.waset.org/abstracts/search?q=hidden%20markov%20model%20%28HMM%29" title=" hidden markov model (HMM)"> hidden markov model (HMM)</a>, <a href="https://publications.waset.org/abstracts/search?q=support%20vector%20machine%20%28SVM%29" title=" support vector machine (SVM)"> support vector machine (SVM)</a> </p> <a href="https://publications.waset.org/abstracts/37296/the-optimum-mel-frequency-cepstral-coefficients-mfccs-contribution-to-iranian-traditional-music-genre-classification-by-instrumental-features" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37296.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">450</span> </span> </div> 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Search results for: S. Haghipour