  Extensive works have tackled Language Identification (LID) in the speech
domain, however their application to the singing voice trails and performances
on Singing Language Identification (SLID) can be improved leveraging recent
progresses made in other singing related tasks. This work presents a modernized
phonotactic system for SLID on polyphonic music: phoneme recognition is
performed with a Connectionist Temporal Classification (CTC)-based acoustic
model trained with multilingual data, before language classification with a
recurrent model based on the phonemes estimation. The full pipeline is trained
and evaluated with a large and publicly available dataset, with unprecedented
performances. First results of SLID with out-of-set languages are also
presented.
