Comunicació presentada al Fourth International Workshop on Folk Music Analysis (FMA2014), celebrat els dies 12 i 13 de juny de 2014 a Istanbul, Turquia.

We apply a lyrics-to-audio alignment state-of-the-art approach to polyphonic pieces from classical Turkish repertoire. A phonetic recognizer is employed, whereby each phoneme is assigned a hidden Markov model (HMM). Initially trained on speech, the models are adapted on singing voice to match the acoustic characteristics of the test dataset. Being the first study on lyrics-to-audio alignment applied on Turkish music, it could serve as a baseline for singing material with similar musical characteristics. As part of this work a dataset of recordings from the classical music tradition is compiled. Experiments, conducted separately for male and female singers, show that female singing is aligned more accurately.

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).