79 citations · 217 across the 13 of their papers we have counts for
15 papers
What Does the Speaker Embedding Encode?
Shuai Wang, Yanmin Qian, Kai Yu
Developing a good speaker embedding has received tremendous interest in the speech community, with representations such as i-vector and d-vector demonstrating remarkable performanc…
Text adaptation for speaker verification with speaker-text factorized embeddings
Yexin Yang, Shuai Wang, Xun Gong +2
Text mismatch between pre-collected data, either training data or enrollment data, and the actual test data can significantly hurt text-dependent speaker verification (SV) system p…
Multi-Step Prediction and Control of Hierarchical Emotion Distribution in Text-to-Speech Synthesis
Sho Inoue, Kun Zhou, Shuai Wang +1
We investigate hierarchical emotion distribution (ED) for achieving multi-level quantitative control of emotion rendering in text-to-speech synthesis (TTS). We introduce a novel mu…
Attention-based Encoder-Decoder End-to-End Neural Diarization with Embedding Enhancer
Zhengyang Chen, Bing Han, Shuai Wang +1
Deep neural network-based systems have significantly improved the performance of speaker diarization tasks. However, end-to-end neural diarization (EEND) systems often struggle to…
Attention-based Encoder-Decoder Network for End-to-End Neural Speaker Diarization with Target Speaker Attractor
Zhengyang Chen, Bing Han, Shuai Wang +1
This paper proposes a novel Attention-based Encoder-Decoder network for End-to-End Neural speaker Diarization (AED-EEND). In AED-EEND system, we incorporate the target speaker enro…
Wespeaker: A Research and Production oriented Speaker Embedding Learning Toolkit
Hongji Wang, Chengdong Liang, Shuai Wang +5
Speaker modeling is essential for many related tasks, such as speaker recognition and speaker diarization. The dominant modeling approach is fixed-dimensional vector representation…
Self-Supervised Learning Based Domain Adaptation for Robust Speaker Verification
Zhengyang Chen, Shuai Wang, Yanmin Qian
Large performance degradation is often observed for speaker ver-ification systems when applied to a new domain dataset. Givenan unlabeled target-domain dataset, unsupervised domain…
Voice activity detection in the wild: A data-driven approach using teacher-student training
Heinrich Dinkel, Shuai Wang, Xuenan Xu +2
Voice activity detection is an essential pre-processing component for speech-related tasks such as automatic speech recognition (ASR). Traditional supervised VAD systems obtain fra…
Unit selection synthesis based data augmentation for fixed phrase speaker verification
Houjun Huang, Xu Xiang, Fei Zhao +2
Data augmentation is commonly used to help build a robust speaker verification system, especially in limited-resource case. However, conventional data augmentation methods usually…
End-to-End Speaker-Dependent Voice Activity Detection
Yefei Chen, Shuai Wang, Yanmin Qian +1
Voice activity detection (VAD) is an essential pre-processing step for tasks such as automatic speech recognition (ASR) and speaker recognition. A basic goal is to remove silent se…
BUT System for the Second DIHARD Speech Diarization Challenge
Federico Landini, Shuai Wang, Mireia Diez +9
This paper describes the winning systems developed by the BUT team for the four tracks of the Second DIHARD Speech Diarization Challenge. For tracks 1 and 2 the systems were mainly…
BUT System Description for DIHARD Speech Diarization Challenge 2019
Federico Landini, Shuai Wang, Mireia Diez +8
This paper describes the systems developed by the BUT team for the four tracks of the second DIHARD speech diarization challenge. For tracks 1 and 2 the systems were based on perfo…
BUT System Description to VoxCeleb Speaker Recognition Challenge 2019
Hossein Zeinali, Shuai Wang, Anna Silnova +2
In this report, we describe the submission of Brno University of Technology (BUT) team to the VoxCeleb Speaker Recognition Challenge (VoxSRC) 2019. We also provide a brief analysis…
Margin Matters: Towards More Discriminative Deep Neural Network Embeddings for Speaker Recognition
Xu Xiang, Shuai Wang, Houjun Huang +2
Recently, speaker embeddings extracted from a speaker discriminative deep neural network (DNN) yield better performance than the conventional methods such as i-vector. In most case…
Deep Discriminant Analysis for i-vector Based Robust Speaker Recognition
Shuai Wang, Zili Huang, Yanmin Qian +1
Linear Discriminant Analysis (LDA) has been used as a standard post-processing procedure in many state-of-the-art speaker recognition tasks. Through maximizing the inter-speaker di…