1.9k citations · 3.6k across the 72 of their papers we have counts for
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An End-to-End Multi-Module Audio Deepfake Generation System for ADD Challenge 2023
Sheng Zhao, Qilong Yuan, Yibo Duan +1
The task of synthetic speech generation is to generate language content from a given text, then simulating fake human voice.The key factors that determine the effect of synthetic s…
The Microsoft System for VoxCeleb Speaker Recognition Challenge 2022
Gang Liu, Tianyan Zhou, Yong Zhao +4
In this report, we describe our submitted system for track 2 of the VoxCeleb Speaker Recognition Challenge 2022 (VoxSRC-22). We fuse a variety of good-performing models ranging fro…
AISHELL-4: An Open Source Dataset for Speech Enhancement, Separation, Recognition and Speaker Diarization in Conference Scenario
Yihui Fu, Luyao Cheng, Shubo Lv +10
In this paper, we present AISHELL-4, a sizable real-recorded Mandarin speech dataset collected by 8-channel circular microphone array for speech processing in conference scenario.…
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…
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…
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…
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…
Cracking the cocktail party problem by multi-beam deep attractor network
Zhuo Chen, Jinyu Li, Xiong Xiao +4
While recent progresses in neural network approaches to single-channel speech separation, or more generally the cocktail party problem, achieved significant improvement, their perf…
Speaker-independent Speech Separation with Deep Attractor Network
Yi Luo, Zhuo Chen, Nima Mesgarani
Despite the recent success of deep learning for many speech processing tasks, single-microphone, speaker-independent speech separation remains challenging for two main reasons. The…
Deep attractor network for single-microphone speaker separation
Zhuo Chen, Yi Luo, Nima Mesgarani
Despite the overwhelming success of deep learning in various speech processing tasks, the problem of separating simultaneous speakers in a mixture remains challenging. Two major di…