Blind Signal Decompositions for Automatic Transcription of Polyphonic Music: NMF and K-SVD on the Benchmark
暂无分享,去创建一个
[1] Jean-Francois Cardoso,et al. Blind signal separation: statistical principles , 1998, Proc. IEEE.
[2] H. Sebastian Seung,et al. Algorithms for Non-negative Matrix Factorization , 2000, NIPS.
[3] P. Smaragdis,et al. Non-negative matrix factorization for polyphonic music transcription , 2003, 2003 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (IEEE Cat. No.03TH8684).
[4] Anssi Klapuri,et al. AUTOMATIC TRANSCRIPTION OF MUSIC , 2003 .
[5] Mark B. Sandler,et al. Automatic Piano Transcription Using Frequency and Time-Domain Information , 2006, IEEE Transactions on Audio, Speech, and Language Processing.
[6] H. Sebastian Seung,et al. Learning the parts of objects by non-negative matrix factorization , 1999, Nature.
[7] Mark D. Plumbley,et al. Unsupervised analysis of polyphonic music by sparse coding , 2006, IEEE Transactions on Neural Networks.
[8] Michael Elad,et al. K-SVD and its non-negative variant for dictionary design , 2005, SPIE Optics + Photonics.
[9] Mark D. Plumbley. Algorithms for nonnegative independent component analysis , 2003, IEEE Trans. Neural Networks.
[10] Masataka Goto,et al. RWC Music Database: Popular, Classical and Jazz Music Databases , 2002, ISMIR.
[11] Mark D. Plumbley,et al. Automatic Music Transcription and Audio Source Separation , 2002, Cybern. Syst..
[12] Mark B. Sandler,et al. Techniques for Automatic Music Transcription , 2000, ISMIR.
[13] Daniel P. W. Ellis,et al. A Discriminative Model for Polyphonic Piano Transcription , 2007, EURASIP J. Adv. Signal Process..