M. Aharon, M. Elad, and A. A. Bruckstein, K- SVD: An algorithm for designing overcomplete dictionaries for sparse representation, IEEE Transactions on Signal Processing, pp.4311-4322, 2006.

S. Araki, A. Ozerov, V. Gowreesunker, H. Sawada, F. Theis et al., The 2010 Signal Separation Evaluation Campaign (SiSEC2010): Audio Source Separation, Proc. of LVA/ICA, pp.114-122, 2010.
DOI : 10.1007/978-3-642-15995-4_15
URL : https://hal.archives-ouvertes.fr/inria-00553385

J. J. Aucouturier and F. Pachet, Representing Musical Genre: A State of the Art, Journal of New Music Research, vol.32, issue.1, pp.83-93, 2003.
DOI : 10.1076/jnmr.32.1.83.16801

R. Bittner, J. Salamon, M. Tierney, M. Mauch, C. Cannam et al., MedleyDB: A multitrack dataset for annotation-intensive MIR research, Proc. of ISMIR, 2014.

F. Canadas-quesada, P. Vera-candeas, N. Ruiz-reyes, and J. , Carabias-Orti, and P. Cabanas-Molero. Percussive/harmonic sound separation by non-negative matrix factorization with smoothness/sparseness constraints, Speech, and Music Processing, pp.1-17, 2014.

D. Ellis, Beat Tracking by Dynamic Programming, Journal of New Music Research, vol.51, issue.1, pp.51-60, 2007.
DOI : 10.1155/2007/67215

S. Ewert and M. Müller, Score-informed source separation for music signals. Multimodal music processing, pp.73-94, 2012.

D. Fitzgerald, Harmonic/percussive separation using median filtering, Proc. of DAFx, 2010.

D. Fitzgerald, Upmixing from mono - A source separation approach, 2011 17th International Conference on Digital Signal Processing (DSP), pp.1-7, 2011.
DOI : 10.1109/ICDSP.2011.6004991

A. Gersho and R. M. Gray, Vector quantization and signal compression, 2012.
DOI : 10.1007/978-1-4615-3626-0

O. Gillet and G. Richard, Enst-drums: an extensive audio-visual database for drum signals processing, Proc. of ISMIR, pp.156-159, 2006.

R. Hennequin, B. David, and R. Badeau, Score informed audio source separation using a parametric model of non-negative spectrogram, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011.
DOI : 10.1109/ICASSP.2011.5946324
URL : https://hal.archives-ouvertes.fr/hal-00945294

J. Hockman, M. Davies, and I. Fujinaga, One in the jungle: Downbeat detection in hardcore, jungle, and drum and bass, Proc. of ISMIR, pp.169-174, 2012.

C. Hsu, D. Wang, J. R. Jang, and K. Hu, A Tandem Algorithm for Singing Pitch Extraction and Voice Separation From Music Accompaniment, IEEE Transactions on Audio, Speech, and Language Processing, vol.20, issue.5, pp.1482-1491, 2012.
DOI : 10.1109/TASL.2011.2182510

P. Huang, S. D. Chen, P. Smaragdis, and M. Hasegawa-johnson, Singing-voice separation from monaural recordings using robust principal component analysis, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
DOI : 10.1109/ICASSP.2012.6287816

X. Jaureguiberry, P. Leveau, S. Maller, and J. Burred, Adaptation of source-specific dictionaries in nonnegative matrix factorization for source separation, Proc. of IEEE ICASSP, pp.5-8, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00868399

M. Kim, J. Yoo, K. Kang, and S. Choi, Nonnegative Matrix Partial Co-Factorization for Spectral and Temporal Drum Source Separation, IEEE Journal of Selected Topics in Signal Processing, vol.5, issue.6, pp.1192-1204, 2011.
DOI : 10.1109/JSTSP.2011.2158803

]. A. Lampropoulos, P. Lampropoulou, and G. Tsihrintzis, Musical genre classification enhanced by improved source separation technique, Proc. of ISMIR, pp.576-581, 2005.

C. Laroche, M. Kowalski, H. Papadopoulous, and G. Richard, Structured projective non negative matrix factorization with drum dictionaries for harmonic/percussive source separation

C. Laroche, M. Kowalski, H. Papadopoulous, and G. Richard, A structured nonnegative matrix factorization for source separation, 2015 23rd European Signal Processing Conference (EUSIPCO), 2015.
DOI : 10.1109/EUSIPCO.2015.7362741
URL : https://hal.archives-ouvertes.fr/hal-01199631

D. Lee and S. Seung, Learning the parts of objects by nonnegative matrix factorization, Nature, pp.788-791, 1999.

D. Lee and S. Seung, Algorithms for non-negative matrix factorization, Proc. of NIPS, pp.556-562, 2001.

K. Lee and M. Slaney, Acoustic Chord Transcription and Key Extraction From Audio Using Key-Dependent HMMs Trained on Synthesized Audio, IEEE Transactions on Audio, Speech, and Language Processing, vol.16, issue.2, pp.291-301, 2008.
DOI : 10.1109/TASL.2007.914399

T. Li, M. Ogihara, and Q. Li, A comparative study on content-based music genre classification, Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval , SIGIR '03, pp.282-289, 2003.
DOI : 10.1145/860435.860487

A. Liutkus and R. Badeau, Generalized Wiener filtering with fractional power spectrograms, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.266-270, 2015.
DOI : 10.1109/ICASSP.2015.7177973
URL : https://hal.archives-ouvertes.fr/hal-01110028

C. Mckay and I. Fujinaga, Musical genre classification: Is it worth pursuing and how can it be improved?, Proc. of ISMIR, pp.101-106, 2006.

Y. Ni, M. Mcvicar, R. Santos-rodriguez, and T. De-bie, Using hyper-genre training to explore genre information for automatic chord estimation, Proc. of ISMIR, pp.109-114, 2012.

N. Ono, K. Miyamoto, J. Le-roux, H. Kameoka, and S. Sagayama, Separation of a monaural audio signal into harmonic/percussive components by complementary diffusion on spectrogram, Proc. of EUSIPCO, 2008.

J. Paulus and T. Virtanen, Drum transcription with non-negative spectrogram factorisation, Proc. of EUSIPCO, pp.1-4, 2005.

H. Rump, S. Miyabe, E. Tsunoo, N. Ono, and S. Sagayama, Autoregressive mfcc models for genre classification improved by harmonic-percussion separation, Proc. of ISMIR, pp.87-92, 2010.

M. N. Schmidt and R. K. Olsson, Single-channel speech separation using sparse non-negative matrix factorization, Proc. of INTERSPEECH, 2006.

P. Smaragdis and J. Brown, Non-negative matrix factorization for polyphonic music transcription, 2003 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (IEEE Cat. No.03TH8684), pp.177-180, 2003.
DOI : 10.1109/ASPAA.2003.1285860

I. To?i´to?i´c and P. Frossard, Dictionary learning, IEEE Transactions on Signal Processing, pp.27-38, 2011.

G. Tzanetakis and P. Cook, Musical genre classification of audio signals, IEEE transactions on Speech and Audio Processing, pp.293-302, 2002.
DOI : 10.1109/TSA.2002.800560

E. Vincent, N. Bertin, and R. Badeau, Adaptive Harmonic Spectral Decomposition for Multiple Pitch Estimation, IEEE Transactions on Audio, Speech, and Language Processing, vol.18, issue.3, pp.528-537, 2010.
DOI : 10.1109/TASL.2009.2034186
URL : https://hal.archives-ouvertes.fr/inria-00350163

E. Vincent, R. Gribonval, and C. Févotte, Performance measurement in blind audio source separation, IEEE Transactions on Audio, Speech and Language Processing, vol.14, issue.4, pp.1462-1469, 2006.
DOI : 10.1109/TSA.2005.858005
URL : https://hal.archives-ouvertes.fr/inria-00544230

C. Wu and A. Lerch, Drum transcription using partially fixed non-negative matrix factorization, 2015 23rd European Signal Processing Conference (EUSIPCO), 2008.
DOI : 10.1109/EUSIPCO.2015.7362590

Z. Yuan and E. Oja, Projective Nonnegative Matrix Factorization for Image Compression and Feature Extraction, Image Analysis, pp.333-342, 2005.
DOI : 10.1007/11499145_35

Q. Zhang and B. Li, Discriminative K-SVD for dictionary learning in face recognition, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.2691-2698, 2010.
DOI : 10.1109/CVPR.2010.5539989