15 citations · 27 across the 11 of their papers we have counts for
9 papers · 1 filter
Endpoint Detection for Streaming End-to-End Multi-talker ASR
Liang Lu, Jinyu Li, Yifan Gong
Streaming end-to-end multi-talker speech recognition aims at transcribing the overlapped speech from conversations or meetings with an all-neural model in a streaming fashion, whic…
Minimum Word Error Rate Training with Language Model Fusion for End-to-End Speech Recognition
Zhong Meng, Yu Wu, Naoyuki Kanda +6
Integrating external language models (LMs) into end-to-end (E2E) models remains a challenging task for domain-adaptive speech recognition. Recently, internal language model estimat…
Internal Language Model Training for Domain-Adaptive End-to-End Speech Recognition
Zhong Meng, Naoyuki Kanda, Yashesh Gaur +6
The efficacy of external language model (LM) integration with existing end-to-end (E2E) automatic speech recognition (ASR) systems can be improved significantly using the internal…
Minimum Bayes Risk Training for End-to-End Speaker-Attributed ASR
Naoyuki Kanda, Zhong Meng, Liang Lu +4
Recently, an end-to-end speaker-attributed automatic speech recognition (E2E SA-ASR) model was proposed as a joint model of speaker counting, speech recognition and speaker identif…
Internal Language Model Estimation for Domain-Adaptive End-to-End Speech Recognition
Zhong Meng, Sarangarajan Parthasarathy, Eric Sun +7
The external language models (LM) integration remains a challenging task for end-to-end (E2E) automatic speech recognition (ASR) which has no clear division between acoustic and la…
Exploring Transformers for Large-Scale Speech Recognition
Liang Lu, Changliang Liu, Jinyu Li +1
While recurrent neural networks still largely define state-of-the-art speech recognition systems, the Transformer network has been proven to be a competitive alternative, especiall…