Exploring the limits of decoder-only models trained on public speech recognition corpora

The emergence of industrial-scale speech recognition (ASR) models such as Whisper and USM, trained on 1M hours of weakly labelled and 12M hours of audio only proprietary data respectively, has led to a stronger need for large scale public ASR corpora and competitive open source pipelines. Unlike the said models, large language models are typically based on Transformer decoders, and it remains unclear if decoder-only models trained on public data alone can deliver competitive performance. In this work, we investigate …

asr audio cs.cl cs.sd data decoder eess.as emergence industrial open source pipelines proprietary public public speech recognition scale speech speech recognition whisper