41 citations · 104 across the 27 of their papers we have counts for
18 papers · 1 filter
Training Text-to-Speech Model with Purely Synthetic Data: Feasibility, Sensitivity, and Generalization Capability
Tingxiao Zhou, Leying Zhang, Zhengyang Chen +1
The potential of synthetic data in text-to-speech (TTS) model training has gained increasing attention, yet its rationality and effectiveness require systematic validation. In this…
Advanced Zero-Shot Text-to-Speech for Background Removal and Preservation with Controllable Masked Speech Prediction
Leying Zhang, Wangyou Zhang, Zhengyang Chen +1
The acoustic background plays a crucial role in natural conversation. It provides context and helps listeners understand the environment, but a strong background makes it difficult…
Data-Efficient Low-Complexity Acoustic Scene Classification via Distilling and Progressive Pruning
Bing Han, Wen Huang, Zhengyang Chen +7
The goal of the acoustic scene classification (ASC) task is to classify recordings into one of the predefined acoustic scene classes. However, in real-world scenarios, ASC systems…
Flow-TSVAD: Target-Speaker Voice Activity Detection via Latent Flow Matching
Zhengyang Chen, Bing Han, Shuai Wang +2
Speaker diarization is typically considered a discriminative task, using discriminative approaches to produce fixed diarization results. In this paper, we explore the use of neural…
Disentangling the Prosody and Semantic Information with Pre-trained Model for In-Context Learning based Zero-Shot Voice Conversion
Zhengyang Chen, Shuai Wang, Mingyang Zhang +3
Voice conversion (VC) aims to modify the speaker's timbre while retaining speech content. Previous approaches have tokenized the outputs from self-supervised into semantic tokens,…
Generating Speakers by Prompting Listener Impressions for Pre-trained Multi-Speaker Text-to-Speech Systems
Zhengyang Chen, Xuechen Liu, Erica Cooper +2
This paper proposes a speech synthesis system that allows users to specify and control the acoustic characteristics of a speaker by means of prompts describing the speaker's traits…
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…
Self-Supervised Learning with Cluster-Aware-DINO for High-Performance Robust Speaker Verification
Bing Han, Zhengyang Chen, Yanmin Qian
Automatic speaker verification task has made great achievements using deep learning approaches with the large-scale manually annotated dataset. However, it's very difficult and exp…
A comprehensive study on self-supervised distillation for speaker representation learning
Zhengyang Chen, Yao Qian, Bing Han +2
In real application scenarios, it is often challenging to obtain a large amount of labeled data for speaker representation learning due to speaker privacy concerns. Self-supervised…
Build a SRE Challenge System: Lessons from VoxSRC 2022 and CNSRC 2022
Zhengyang Chen, Bing Han, Xu Xiang +3
Many speaker recognition challenges have been held to assess the speaker verification system in the wild and probe the performance limit. Voxceleb Speaker Recognition Challenge (Vo…
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…
SJTU-AISPEECH System for VoxCeleb Speaker Recognition Challenge 2022
Zhengyang Chen, Bing Han, Xu Xiang +3
This report describes the SJTU-AISPEECH system for the Voxceleb Speaker Recognition Challenge 2022. For track1, we implemented two kinds of systems, the online system and the offli…
The SJTU System for Short-duration Speaker Verification Challenge 2021
Bing Han, Zhengyang Chen, Zhikai Zhou +1
This paper presents the SJTU system for both text-dependent and text-independent tasks in short-duration speaker verification (SdSV) challenge 2021. In this challenge, we explored…
Self-Supervised Speaker Verification Using Dynamic Loss-Gate and Label Correction
Bing Han, Zhengyang Chen, Yanmin Qian
For self-supervised speaker verification, the quality of pseudo labels decides the upper bound of the system due to the massive unreliable labels. In this work, we propose dynamic…
The SJTU X-LANCE Lab System for CNSRC 2022
Zhengyang Chen, Bei Liu, Bing Han +2
This technical report describes the SJTU X-LANCE Lab system for the three tracks in CNSRC 2022. In this challenge, we explored the speaker embedding modeling ability of deep ResNet…
Large-scale Self-Supervised Speech Representation Learning for Automatic Speaker Verification
Zhengyang Chen, Sanyuan Chen, Yu Wu +5
The speech representations learned from large-scale unlabeled data have shown better generalizability than those from supervised learning and thus attract a lot of interest to be a…
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…