184 citations · 203 across the 6 of their papers we have counts for
3 papers · 1 filter
Knowledge Transfer from Large-scale Pretrained Language Models to End-to-end Speech Recognizers
Yotaro Kubo, Shigeki Karita, Michiel Bacchiani
End-to-end speech recognition is a promising technology for enabling compact automatic speech recognition (ASR) systems since it can unify the acoustic and language model into a si…
A Comparative Study on Neural Architectures and Training Methods for Japanese Speech Recognition
Shigeki Karita, Yotaro Kubo, Michiel Adriaan Unico Bacchiani +1
End-to-end (E2E) modeling is advantageous for automatic speech recognition (ASR) especially for Japanese since word-based tokenization of Japanese is not trivial, and E2E modeling…
Toward domain-invariant speech recognition via large scale training
Arun Narayanan, Ananya Misra, Khe Chai Sim +6
Current state-of-the-art automatic speech recognition systems are trained to work in specific `domains', defined based on factors like application, sampling rate and codec. When su…