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Bangla Music Genre Classification Using Neural Network

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dc.contributor.author Al Mamun, Md. Afif
dc.contributor.author Kadir, Imamul
dc.contributor.author Rabby, AKM Shahariar Azad
dc.contributor.author Al Azmi, Abdullah
dc.date.accessioned 2022-01-12T05:26:05Z
dc.date.available 2022-01-12T05:26:05Z
dc.date.issued 2019-11
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6713
dc.description.abstract Music genre classification is very vital for music recommendation and for the retrieval of music information. So many works have already been done for classifying genres of English music using different machine learning approaches. Even though Bangla music is very rich in its own fashion, there is almost no notable work found to classify music genres of Bangla music using machine learning techniques yet. There are so many types and styles of Bangla music which can be classified in different genres. Initially, we're considering 6 different Bangla music genres such as `Bangla Adhunik', `Bangla Hip-Hop', `Bangla Band Music', `Nazrulgeeti', `Palligeeti', `Rabindra Sangeet' etc. We are using 250-300 songs (. MP3 files) for each genre. We extracted different time domain and frequency domain features of audio signals from digital audio files (i.e. MP3 files). Finally, in this study, we proposed a deep learning model (after comparing performances of different models) to do a multiclass classification of Bangla music genres. en_US
dc.language.iso en_US en_US
dc.publisher IEEE en_US
dc.subject Bangla Music Genre Classification en_US
dc.subject Deep Learning en_US
dc.subject Zero Crossing Rate en_US
dc.subject Spectral Centroid en_US
dc.subject MFC (Mel Frequency Cepstral Coefficient) en_US
dc.subject Delta en_US
dc.subject RMSE en_US
dc.subject Chroma Frequency en_US
dc.subject Spectral Roll Off en_US
dc.subject Neural Network en_US
dc.title Bangla Music Genre Classification Using Neural Network en_US
dc.type Article en_US


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