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Volumn , Issue , 2008, Pages 17-22

Combining Pitch-Based Inference and Non-Negative Spectrogram Factorization in Separating Vocals from Polyphonic Music

Author keywords

non negative matrix factorization; pitch estimation; Sound source separation; unsupervised learning

Indexed keywords

ACOUSTIC NOISE; ACOUSTIC VARIABLES MEASUREMENT; CONTINUOUS SPEECH RECOGNITION; MATRIX ALGEBRA; MUSIC; MUSICAL INSTRUMENTS; SEPARATION; SOURCE SEPARATION; SPECTROGRAPHS; UNSUPERVISED LEARNING;

EID: 84946031315     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (63)

References (12)
  • 2
    • 4644242508 scopus 로고    scopus 로고
    • A real-time music-scene-description system: predominant-f0 estimation for detecting melody and bass lines in real-world audio signals
    • M. Goto, "A real-time music-scene-description system: predominant-f0 estimation for detecting melody and bass lines in real-world audio signals," Speech Communication, vol. 43, no. 4, 2004.
    • (2004) Speech Communication , vol.43 , Issue.4
    • Goto, M.1
  • 3
    • 34547508425 scopus 로고    scopus 로고
    • Automatic synchronization between lyrics and music CD recordings based on Viterbi alignment of segregated vocal signals
    • San Diego, USA
    • H. Fujihara, M. Goto, J. Ogata, K. Komatani, T. Ogata, and H. G. Okuno, "Automatic synchronization between lyrics and music CD recordings based on Viterbi alignment of segregated vocal signals," in IEEE International Symposium on Multimedia, San Diego, USA, 2006.
    • (2006) IEEE International Symposium on Multimedia
    • Fujihara, H.1    Goto, M.2    Ogata, J.3    Komatani, K.4    Ogata, T.5    Okuno, H. G.6
  • 4
    • 50249152311 scopus 로고    scopus 로고
    • Monaural sound source separation by non-negative matrix factorization with temporal continuity and sparseness criteria
    • T. Virtanen, "Monaural sound source separation by non-negative matrix factorization with temporal continuity and sparseness criteria," IEEE Transactions on Audio, Speech, and Language Processing, vol. 15, no. 3, 2007.
    • (2007) IEEE Transactions on Audio, Speech, and Language Processing , vol.15 , Issue.3
    • Virtanen, T.1
  • 6
    • 51449094735 scopus 로고    scopus 로고
    • Adaptation of Bayesian models for single channel source separation and its application to voice / music separation in popular songs
    • A. Ozerov, P. Philippe, F. Bimbot, and R. Gribonval, "Adaptation of Bayesian models for single channel source separation and its application to voice / music separation in popular songs," IEEE Transactions on Audio, Speech, and Language Processing, vol. 15, no. 5, 2007.
    • (2007) IEEE Transactions on Audio, Speech, and Language Processing , vol.15 , Issue.5
    • Ozerov, A.1    Philippe, P.2    Bimbot, F.3    Gribonval, R.4
  • 7
    • 54249122834 scopus 로고    scopus 로고
    • Automatic transcription ofmelody, bass line, and chords in polyphonic music
    • to appear
    • M. Ryynänen and A. Klapuri, "Automatic transcription ofmelody, bass line, and chords in polyphonic music," Computer Music Journal, vol. 32, no. 3, 2008, to appear.
    • (2008) Computer Music Journal , vol.32 , Issue.3
    • Ryynänen, M.1    Klapuri, A.2
  • 11
    • 51449099173 scopus 로고    scopus 로고
    • Three techniques for improving automatic synchronization between music and lyrics: Fricative detection, filler model, and novel feature vectors for vocal activity detection
    • Las Vegas, USA
    • H. Fujihara and M. Goto, "Three techniques for improving automatic synchronization between music and lyrics: Fricative detection, filler model, and novel feature vectors for vocal activity detection," in Proceedings of IEEE International Conference on Audio, Speech and Signal Processing, Las Vegas, USA, 2008.
    • (2008) Proceedings of IEEE International Conference on Audio, Speech and Signal Processing
    • Fujihara, H.1    Goto, M.2
  • 12
    • 4243101253 scopus 로고    scopus 로고
    • Cambridge University Engineering Department
    • Cambridge University Engineering Department. The Hidden Markov Model Toolkit (HTK), http://htk.eng.cam.ac.uk/.
    • The Hidden Markov Model Toolkit (HTK)


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.