116 citations · 911 across the 43 of their papers we have counts for
12 papers · 1 filter
Separating Long-Form Speech with Group-Wise Permutation Invariant Training
Wangyou Zhang, Zhuo Chen, Naoyuki Kanda +8
Multi-talker conversational speech processing has drawn many interests for various applications such as meeting transcription. Speech separation is often required to handle overlap…
Continuous Speech Separation with Recurrent Selective Attention Network
Yixuan Zhang, Zhuo Chen, Jian Wu +4
While permutation invariant training (PIT) based continuous speech separation (CSS) significantly improves the conversation transcription accuracy, it often suffers from speech lea…
Factorized Neural Transducer for Efficient Language Model Adaptation
Xie Chen, Zhong Meng, Sarangarajan Parthasarathy +1
In recent years, end-to-end (E2E) based automatic speech recognition (ASR) systems have achieved great success due to their simplicity and promising performance. Neural Transducer…
Internal Language Model Adaptation with Text-Only Data for End-to-End Speech Recognition
Zhong Meng, Yashesh Gaur, Naoyuki Kanda +4
Text-only adaptation of an end-to-end (E2E) model remains a challenging task for automatic speech recognition (ASR). Language model (LM) fusion-based approaches require an addition…
Transcribe-to-Diarize: Neural Speaker Diarization for Unlimited Number of Speakers using End-to-End Speaker-Attributed ASR
Naoyuki Kanda, Xiong Xiao, Yashesh Gaur +4
This paper presents Transcribe-to-Diarize, a new approach for neural speaker diarization that uses an end-to-end (E2E) speaker-attributed automatic speech recognition (SA-ASR). The…
A Comparative Study of Modular and Joint Approaches for Speaker-Attributed ASR on Monaural Long-Form Audio
Naoyuki Kanda, Xiong Xiao, Jian Wu +6
Speaker-attributed automatic speech recognition (SA-ASR) is a task to recognize "who spoke what" from multi-talker recordings. An SA-ASR system usually consists of multiple modules…
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…
Large-Scale Pre-Training of End-to-End Multi-Talker ASR for Meeting Transcription with Single Distant Microphone
Naoyuki Kanda, Guoli Ye, Yu Wu +5
Transcribing meetings containing overlapped speech with only a single distant microphone (SDM) has been one of the most challenging problems for automatic speech recognition (ASR).…
End-to-End Speaker-Attributed ASR with Transformer
Naoyuki Kanda, Guoli Ye, Yashesh Gaur +4
This paper presents our recent effort on end-to-end speaker-attributed automatic speech recognition, which jointly performs speaker counting, speech recognition and speaker identif…
Continuous Speech Separation with Ad Hoc Microphone Arrays
Dongmei Wang, Takuya Yoshioka, Zhuo Chen +3
Speech separation has been shown effective for multi-talker speech recognition. Under the ad hoc microphone array setup where the array consists of spatially distributed asynchrono…
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…
Hypothesis Stitcher for End-to-End Speaker-attributed ASR on Long-form Multi-talker Recordings
Xuankai Chang, Naoyuki Kanda, Yashesh Gaur +3
An end-to-end (E2E) speaker-attributed automatic speech recognition (SA-ASR) model was proposed recently to jointly perform speaker counting, speech recognition and speaker identif…