Fetching the paper…
Reading the bibliography…
Automatic lyrics to polyphonic audio alignment is a challenging task not only because the vocals are corrupted by background music, but also there is a lack of annotated polyphonic corpus for effective acoustic modeling.
H. Hermansky and N. Morgan, “Rasta processing of speech,”
1994
Earlier work this paper cites.
A. Loscos, P. Cano, and J. Bonada, “Low-delay singing voice alignment to text.” in
1999
Earlier work this paper cites.
M. J. Carey, E. S. Parris, and H. Lloyd-Thomas, “A comparison of features for speech, music discrimination,” in
1999
Earlier work this paper cites.
T. George, E. Georg, and C. Perry, “Automatic musical genre classification of audio signals,” in
2001
Earlier work this paper cites.
G. Tzanetakis and P. Cook, “Musical genre classification of audio signals,”
2002
Earlier work this paper cites.
M. Mandel and D. Ellis, “Song-level features and support vector machines for music classification,” in
2005
Earlier work this paper cites.
C. Panagiotakis and G. Tziritas, “A speech/music discriminator based on RMS and zero-crossings,”
2005
Earlier work this paper cites.
D. Ellis, “Classifying music audio with timbral and chroma features,” in
2007
Earlier work this paper cites.
M. Ramona, G. Richard, and B. David, “Vocal detection in music with support vector machines,” in
2008
Earlier work this paper cites.
A. Mesaros and T. Virtanen, “Automatic recognition of lyrics in singing,”
2010
Earlier work this paper cites.
F. Eyben, M. Wöllmer, and B. Schuller, “Opensmile: the Munich versatile and fast open-source audio feature extractor,” in
2010
Earlier work this paper cites.
H. Fujihara, M. Goto, J. Ogata, and H. G. Okuno, “Lyricsynchronizer: Automatic synchronization system between musical audio signals and lyrics,”
2011
Earlier work this paper cites.
N. Dehak, P. J. Kenny, R. Dehak, P. Dumouchel, and P. Ouellet, “Front-end factor analysis for speaker verification,”
2011
Earlier work this paper cites.
D. Povey, A. Ghoshal, G. Boulianne, L. Burget, O. Glembek, N. Goel, M. Hannemann, P. Motlicek, Y. Qian, P. Schwarz
2011
Earlier work this paper cites.
M. Mauch, H. Fujihara, and M. Goto, “Integrating additional chord information into HMM-based lyrics-to-audio alignment,”
2012
Cited alongside, same era.
R. J. Zatorre and S. R. Baum, “Musical melody and speech intonation: Singing a different tune,”
2012
Cited alongside, same era.
H. Fujihara and M. Goto, “Lyrics-to-audio alignment and its application,” in
2012
Cited alongside, same era.
J. K. Hansen, “Recognition of phonemes in a-cappella recordings using temporal patterns and mel frequency cepstral coefficients,” in
2012
Cited alongside, same era.
B. Schuller, S. Steidl, A. Batliner, A. Vinciarelli, K. Scherer, F. Ringeval, M. Chetouani, F. Weninger, F. Eyben, E. Marchi
2013
Cited alongside, same era.
J. Böhm, F. Eyben, M. Schmitt, H. Kosch, and B. Schuller, “Seeking the superstar: Automatic assessment of perceived singing quality,” in
2017
Later among the works it cites.
G. Dzhambazov, “Knowledge-based probabilistic modeling for tracking lyrics in music audio signals,” Ph.D. dissertation, Universitat Pompeu Fabra, 2017
2017
Later among the works it cites.
C. Gupta, R. Tong, H. Li, and Y. Wang, “Semi-supervised lyrics and solo-singing alignment,” in
2018
Later among the works it cites.
S. Sing!, “Smule.digital archive mobile performances(damp),”
2018
Later among the works it cites.
C. Gupta, H. Li, and Y. Wang, “Automatic pronunciation evaluation of singing,”
2018
Later among the works it cites.
C.-C. Wang, “Mirex2018: Lyrics-to-audio alignment for instrument accompanied singings,” in
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2013
Cited alongside, same era.
M. McVicar, D. P. Ellis, and M. Goto, “Leveraging repetition for improved automatic lyric transcription in popular music,” in
2014
Cited alongside, same era.
S. Zhang, R. C. Repetto, and X. Serra, “Study of the similarity between linguistic tones and melodic pitch contours in Beijing opera singing.” in
2014
Cited alongside, same era.
J. Li, L. Deng, Y. Gong, and R. Haeb-Umbach, “An overview of noise-robust automatic speech recognition,”
2014
Cited alongside, same era.
G. B. Dzhambazov and X. Serra, “Modeling of phoneme durations for alignment between polyphonic audio and lyrics,” in
2015
Cited alongside, same era.
T. Ko, V. Peddinti, D. Povey, and S. Khudanpur, “Audio augmentation for speech recognition,” in
2015
Cited alongside, same era.
A. M. Kruspe, “Bootstrapping a system for phoneme recognition and keyword spotting in unaccompanied singing,” in
2016
Cited alongside, same era.
2018
Later among the works it cites.
2018
Later among the works it cites.
G. Meseguer-Brocal, A. Cohen-Hadria, and G. Peeters, “Dali: A large dataset of synchronized audio, lyrics and notes, automatically created using teacher-student machine learning paradigm,” in
2018
Later among the works it cites.
D. Povey, G. Cheng, Y. Wang, K. Li, H. Xu, M. Yarmohammadi, and S. Khudanpur, “Semi-orthogonal low-rank matrix factorization for deep neural networks,” in
2018
Later among the works it cites.
D. Stoller, S. Ewert, and S. Dixon, “Wave-u-net: A multi-scale neural network for end-to-end audio source separation,” in
2018
Later among the works it cites.
B. Sharma, C. Gupta, H. Li, and Y. Wang, “Automatic lyrics-to-audio alignment on polyphonic music using singing-adapted acoustic models,” in
2019
Closest in time.
S. E. Daniel Stoller, Simon Durand, “End-to-end lyrics alignment for polyphonic music using an audio-to-character recognition model,” in
2019
Closest in time.
F. A. Raposo, D. M. de Matos, and R. Ribeiro, “An information-theoretic approach to machine-oriented music summarization,”
2019
Closest in time.