1.9k citations · 2k across the 63 of their papers we have counts for
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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…
VarArray: Array-Geometry-Agnostic Continuous Speech Separation
Takuya Yoshioka, Xiaofei Wang, Dongmei Wang +4
Continuous speech separation using a microphone array was shown to be promising in dealing with the speech overlap problem in natural conversation transcription. This paper propose…
All-neural beamformer for continuous speech separation
Zhuohuang Zhang, Takuya Yoshioka, Naoyuki Kanda +4
Continuous speech separation (CSS) aims to separate overlapping voices from a continuous influx of conversational audio containing an unknown number of utterances spoken by an unkn…
WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing
Sanyuan Chen, Chengyi Wang, Zhengyang Chen +15
Self-supervised learning (SSL) achieves great success in speech recognition, while limited exploration has been attempted for other speech processing tasks. As speech signal contai…
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…
Investigation of Practical Aspects of Single Channel Speech Separation for ASR
Jian Wu, Zhuo Chen, Sanyuan Chen +5
Speech separation has been successfully applied as a frontend processing module of conversation transcription systems thanks to its ability to handle overlapped speech and its flex…
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…
Streaming Multi-talker Speech Recognition with Joint Speaker Identification
Liang Lu, Naoyuki Kanda, Jinyu Li +1
In multi-talker scenarios such as meetings and conversations, speech processing systems are usually required to transcribe the audio as well as identify the speakers for downstream…
Speech-language Pre-training for End-to-end Spoken Language Understanding
Yao Qian, Ximo Bian, Yu Shi +4
End-to-end (E2E) spoken language understanding (SLU) can infer semantics directly from speech signal without cascading an automatic speech recognizer (ASR) with a natural language…
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…
A Review of Speaker Diarization: Recent Advances with Deep Learning
Tae Jin Park, Naoyuki Kanda, Dimitrios Dimitriadis +3
Speaker diarization is a task to label audio or video recordings with classes that correspond to speaker identity, or in short, a task to identify "who spoke when". In the early ye…