activity
20192022
most citedDistilling the Knowledge of BERT for CTC-based ASR

6 citations · 10 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2021

ASR Rescoring and Confidence Estimation with ELECTRA

Hayato Futami, Hirofumi Inaguma, Masato Mimura +2

In automatic speech recognition (ASR) rescoring, the hypothesis with the fewest errors should be selected from the n-best list using a language model (LM). However, LMs are usually…

cs.CL20204 cited

Distilling the Knowledge of BERT for Sequence-to-Sequence ASR

Hayato Futami, Hirofumi Inaguma, Sei Ueno +3

Attention-based sequence-to-sequence (seq2seq) models have achieved promising results in automatic speech recognition (ASR). However, as these models decode in a left-to-right way,…

eess.AS2020

Generative Adversarial Training Data Adaptation for Very Low-resource Automatic Speech Recognition

Kohei Matsuura, Masato Mimura, Shinsuke Sakai +1

It is important to transcribe and archive speech data of endangered languages for preserving heritages of verbal culture and automatic speech recognition (ASR) is a powerful tool t…

cs.CL2020

Speech Corpus of Ainu Folklore and End-to-end Speech Recognition for Ainu Language

Kohei Matsuura, Sei Ueno, Masato Mimura +2

Ainu is an unwritten language that has been spoken by Ainu people who are one of the ethnic groups in Japan. It is recognized as critically endangered by UNESCO and archiving and d…

cs.CL2019

Improving OOV Detection and Resolution with External Language Models in Acoustic-to-Word ASR

Hirofumi Inaguma, Masato Mimura, Shinsuke Sakai +1

Acoustic-to-word (A2W) end-to-end automatic speech recognition (ASR) systems have attracted attention because of an extremely simplified architecture and fast decoding. To alleviat…