5 citations · 9 across the 9 of their papers we have counts for
8 papers · 1 filter
Adapting Multi-Lingual ASR Models for Handling Multiple Talkers
Chenda Li, Yao Qian, Zhuo Chen +5
State-of-the-art large-scale universal speech models (USMs) show a decent automatic speech recognition (ASR) performance across multiple domains and languages. However, it remains…
Target Sound Extraction with Variable Cross-modality Clues
Chenda Li, Yao Qian, Zhuo Chen +5
Automatic target sound extraction (TSE) is a machine learning approach to mimic the human auditory perception capability of attending to a sound source of interest from a mixture o…
Target Speaker Voice Activity Detection with Transformers and Its Integration with End-to-End Neural Diarization
Dongmei Wang, Xiong Xiao, Naoyuki Kanda +2
This paper describes a speaker diarization model based on target speaker voice activity detection (TS-VAD) using transformers. To overcome the original TS-VAD model's drawback of b…
Leveraging Real Conversational Data for Multi-Channel Continuous Speech Separation
Xiaofei Wang, Dongmei Wang, Naoyuki Kanda +2
Existing multi-channel continuous speech separation (CSS) models are heavily dependent on supervised data - either simulated data which causes data mismatch between the training an…
PickNet: Real-Time Channel Selection for Ad Hoc Microphone Arrays
Takuya Yoshioka, Xiaofei Wang, Dongmei Wang
This paper proposes PickNet, a neural network model for real-time channel selection for an ad hoc microphone array consisting of multiple recording devices like cell phones. Assumi…
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…
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…