Sometin Beta Pass Notin: Improving Multilingual ASR for Nigerian Languages via Knowledge Distillation

Although modern multilingual Automatic Speech Recognition (ASR) systems support several Nigerian languages, their performance consistently lags behind resource-rich languages such as English and French. Nigerian languages present unique modelling hurdles, including acute data scarcity, inconsistent orthography, tonal diacritics, diverse accents, frequent code-switching, and localised named entities. To address these challenges, we developed a multilingual ASR framework using a two-stage distillation process. First, we employed student-teacher knowledge distillation from existing monolingual models, conditioned on robust language-specific N-gram language models. Second, we performed iterat...

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