Disentangling speaker and language effects in cross-lingual speaker verification

arXiv·low signal

This paper reduces the performance drop cross-lingual speaker-verification systems suffer when enrollment and test utterances are in different languages, by disentangling speaker identity from language effects, evaluated on Iberian languages. It is a narrow speech-ML result with minimal agent relevance. Included as new, recent primary-source research at low importance. eess.AS/cs.CL.