Automatic identification of music performer using the linear prediction cepstral coefficients method

• Autorzy: Chudy M.
• Konferencja: 12th International Symposium on Sound and Vision Engineering and Mastering (ISSVEM'07), June 15-16, Gdansk, Poland
• Języki publikacji: EN

Abstrakty

EN

The paper describes a method of automatic identification of different music performers playing identical pieces of music on the same instrument. The performers' models based on the LPCC features and vector quantization are proposed as methods of classification. The presented approach was verified with a database of experimental samples of Bach's 1st Cello Suite recorded especially for this study and the original audio CD recordings of Bach's 6 Cello Suites performed by six famous cellists.

Słowa kluczowe

EN

linear prediction cepstral coefficients; music performer identification; vector quantization

• Wydawca: Instytut Podstawowych Problemów Techniki PAN ; Komitet Akustyki PAN ; Polskie Towarzystwo Akustyczne
• Czasopismo: Archives of Acoustics
• Rocznik: 2008
• Tom: Vol. 33, No. 1
• Strony: 27--33
• Opis fizyczny: Bibliogr. 10 poz., tab.

Twórcy

autor

Chudy M.

• Warsaw University of Technology, Institute of Radioelectronics, Nowowiejska 15/19, 00-665 Warszawa, Poland,

Bibliografia

• [1] CHUDY M., System for automatic identification of music performer (System do automatycznego rozpoznawania wykonawcy utworu muzycznego), M.S. Degree thesis, Computer Science Department, Warsaw School of Information Technology, Warsaw 2006.
• [2] CHUDY M., Automatic identification of music performer (Automatyczna identyfikacja wykonawcy utworu muzycznego), Proceedings of the 11th Symposium AES “New Trends in Audio and Video”, p. 170–175, Bialystok 2006.
• [3] FUJIHARA H., KITAHARA T., GOTO M. et al., Singer identification based on accompaniment sound reduction and reliable frame selection, Proceedings of the 6th International Conference on Music Information Retrieval, London 2005.
• [4] GERSHO A., GRAY R., Vector quantization and signal compression, Kluwer Academic Publishers, Boston 1992.
• [5] KIM H. G., BERDAHL E., MOREAU N., SIKORA T., Speaker recognition using MPEG-7 descriptors, Eurospeech-2003, pp. 489–492, Sep. 2003.
• [6] KIM Y. E., WHITMAN B., Singer identification in popular music recordings using voice coding features, Proceedings of the 3rd International Conference on Music Information Retrieval, Paris 2002.
• [7] MCKINNEY M. F., BREEBAART J., Features for audio and music classification, Proceedings of the 4th International Conference on Music Information Retrieval, Baltimore, Maryland (USA) 2003.
• [8] MESAROS A., ASTOLA J., The mel-frequency cepstral coefficients in the context of singer identification, Proceedings of the 6th International Conference on Music Information Retrieval, London 2005.
• [9] NWE T. L., LI H., Exploring vibrato-motivated acoustic features for singer recognition, IEEE Transactions on Audio, Speech, and Language Processing, 15, 2, 519–530 (2007).
• [10] TSAI W. H., WANG H.M., Automatic singer recognition of popular music recordings via estimation and modeling of solo vocal signals, IEEE Transactions on Audio, Speech, and Language Processing, 14, 1, 330–341 (2006).