1.9k citations · 3.6k across the 72 of their papers we have counts for
15 papers · 1 filter
Continuous Speech Separation Using Speaker Inventory for Long Multi-talker Recording
Cong Han, Yi Luo, Chenda Li +8
Leveraging additional speaker information to facilitate speech separation has received increasing attention in recent years. Recent research includes extracting target speech by us…
Exploring End-to-End Multi-channel ASR with Bias Information for Meeting Transcription
Xiaofei Wang, Naoyuki Kanda, Yashesh Gaur +3
Joint optimization of multi-channel front-end and automatic speech recognition (ASR) has attracted much interest. While promising results have been reported for various tasks, past…
Rethinking the Separation Layers in Speech Separation Networks
Yi Luo, Zhuo Chen, Cong Han +3
Modules in all existing speech separation networks can be categorized into single-input-multi-output (SIMO) modules and single-input-single-output (SISO) modules. SIMO modules gene…
ESPnet-se: end-to-end speech enhancement and separation toolkit designed for asr integration
Chenda Li, Jing Shi, Wangyou Zhang +8
We present ESPnet-SE, which is designed for the quick development of speech enhancement and speech separation systems in a single framework, along with the optional downstream spee…
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…
Integration of speech separation, diarization, and recognition for multi-speaker meetings: System description, comparison, and analysis
Desh Raj, Pavel Denisov, Zhuo Chen +11
Multi-speaker speech recognition of unsegmented recordings has diverse applications such as meeting transcription and automatic subtitle generation. With technical advances in syst…
Don't shoot butterfly with rifles: Multi-channel Continuous Speech Separation with Early Exit Transformer
Sanyuan Chen, Yu Wu, Zhuo Chen +3
With its strong modeling capacity that comes from a multi-head and multi-layer structure, Transformer is a very powerful model for learning a sequential representation and has been…
Microsoft Speaker Diarization System for the VoxCeleb Speaker Recognition Challenge 2020
Xiong Xiao, Naoyuki Kanda, Zhuo Chen +10
This paper describes the Microsoft speaker diarization system for monaural multi-talker recordings in the wild, evaluated at the diarization track of the VoxCeleb Speaker Recogniti…
Speaker Separation Using Speaker Inventories and Estimated Speech
Peidong Wang, Zhuo Chen, DeLiang Wang +2
We propose speaker separation using speaker inventories and estimated speech (SSUSIES), a framework leveraging speaker profiles and estimated speech for speaker separation. SSUSIES…
An End-to-end Architecture of Online Multi-channel Speech Separation
Jian Wu, Zhuo Chen, Jinyu Li +5
Multi-speaker speech recognition has been one of the keychallenges in conversation transcription as it breaks the singleactive speaker assumption employed by most state-of-the-arts…
Investigation of End-To-End Speaker-Attributed ASR for Continuous Multi-Talker Recordings
Naoyuki Kanda, Xuankai Chang, Yashesh Gaur +4
Recently, an end-to-end (E2E) speaker-attributed automatic speech recognition (SA-ASR) model was proposed as a joint model of speaker counting, speech recognition and speaker ident…
Continuous Speech Separation with Conformer
Sanyuan Chen, Yu Wu, Zhuo Chen +6
Continuous speech separation plays a vital role in complicated speech related tasks such as conversation transcription. The separation model extracts a single speaker signal from a…
Joint Speaker Counting, Speech Recognition, and Speaker Identification for Overlapped Speech of Any Number of Speakers
Naoyuki Kanda, Yashesh Gaur, Xiaofei Wang +4
We propose an end-to-end speaker-attributed automatic speech recognition model that unifies speaker counting, speech recognition, and speaker identification on monaural overlapped…
Neural Speech Separation Using Spatially Distributed Microphones
Dongmei Wang, Zhuo Chen, Takuya Yoshioka
This paper proposes a neural network based speech separation method using spatially distributed microphones. Unlike with traditional microphone array settings, neither the number o…
Continuous speech separation: dataset and analysis
Zhuo Chen, Takuya Yoshioka, Liang Lu +6
This paper describes a dataset and protocols for evaluating continuous speech separation algorithms. Most prior studies on speech separation use pre-segmented signals of artificial…