5 papers
Interpolating Speaker Identities in Embedding Space for Data Expansion
Tianchi Liu, Ruijie Tao, Qiongqiong Wang +5
The success of deep learning-based speaker verification systems is largely attributed to access to large-scale and diverse speaker identity data. However, collecting data from more…
Context-Aware Two-Step Training Scheme for Domain Invariant Speech Separation
Wupeng Wang, Zexu Pan, Jingru Lin +2
Speech separation seeks to isolate individual speech signals from a multi-talk speech mixture. Despite much progress, a system well-trained on synthetic data often experiences perf…
SA-WavLM: Speaker-Aware Self-Supervised Pre-training for Mixture Speech
Jingru Lin, Meng Ge, Junyi Ao +2
It was shown that pre-trained models with self-supervised learning (SSL) techniques are effective in various downstream speech tasks. However, most such models are trained on singl…
The NUS-HLT System for ICASSP2024 ICMC-ASR Grand Challenge
Meng Ge, Yizhou Peng, Yidi Jiang +6
This paper summarizes our team's efforts in both tracks of the ICMC-ASR Challenge for in-car multi-channel automatic speech recognition. Our submitted systems for ICMC-ASR Challeng…
Selective HuBERT: Self-Supervised Pre-Training for Target Speaker in Clean and Mixture Speech
Jingru Lin, Meng Ge, Wupeng Wang +2
Self-supervised pre-trained speech models were shown effective for various downstream speech processing tasks. Since they are mainly pre-trained to map input speech to pseudo-label…