Comunicació presentada a la 17th International Society for Music Information Retrieval Conference (ISMIR 2016), celebrada els dies 7 a 11 d'agost de 2018 a Nova York, EUA.

In this paper we describe the two algorithms we submitted for the MIREX 2017 task of Automatic Lyrics-to-Audio Alignment. The task has as a goal the automatic detection of word boundaries in multi-instrumental English pop music. We rely on a phonetic recognizer based on hidden Markov models (HMM): a widely-used method for tracking phonemes in speech processing problems. Tracking lyrics in music audio is harder than tracking text in speech because, unlike speech, the singing voice is mixed with multiple instruments. To address this obstacle we propose the application of two separate methods for segregating the singing voice from the multi-instrumental mix. One of them is based on the detection of vocal harmonic partials, whereas the other extracts the vocal content by means of source separation.

This work is partly supported by the European Research Council under the European Union’s Seventh Framework Program, as part of the CompMusic project (ERC grant agreement 267583) and partly by the Spanish Ministry of Economy and Competitiveness, through the ”María de Maeztu” Programme for Centres/Units of Excellence in R&D” (MDM-2015-0502).