Publication: Automatic Transcription of Lyrics in Monophonic and Poliphonic Songs
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2014-09-09
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2014-09-09
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Abstract
The paper proposes the implementation of a system for automatic transcription of lyrics in monophonic and polyphonic songs. The basis of the system is an automatic speech recognizer. Taking into account the differences between singing and spoken voice, acoustic models are adapted to singing voice, using several methods, and Language Models (LM) trained on songs lyrics are built. Moreover, background music is attenuated in polyphonic music using the Robust Principal Component Analysis (RPCA) algorithm, trying to facilitate the recognition task avoiding its effect. The results show that, using
as adaptation data the same type of tracks that are transcribed then, both adaptation methods and specific LM for songs
improve the performance of the baseline system at phonemeand word-level. However, the use of RPCA over polyphonic songs introduces distortions in singing voice, and therefore,
in general, it is not useful for improving the performance of the whole system.
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Automatic lyrics transcription, Singing voice separation, RPCA, Singing adaptation, MLLR, MAP, N-gram language models