Automatic lyrics-to-audio alignment in classical Turkish music

Abstract

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.