6 citations · 6 across the 15 of their papers we have counts for
7 papers · 2 filters
Neural Directed Speech Enhancement with Dual Microphone Array in High Noise Scenario
Wen Wen, Qiang Zhou, Yu Xi +3
In multi-speaker scenarios, leveraging spatial features is essential for enhancing target speech. While with limited microphone arrays, developing a compact multi-channel speech en…
Streaming Keyword Spotting Boosted by Cross-layer Discrimination Consistency
Yu Xi, Haoyu Li, Xiaoyu Gu +3
Connectionist Temporal Classification (CTC), a non-autoregressive training criterion, is widely used in online keyword spotting (KWS). However, existing CTC-based KWS decoding stra…
NTC-KWS: Noise-aware CTC for Robust Keyword Spotting
Yu Xi, Haoyu Li, Hao Li +4
In recent years, there has been a growing interest in designing small-footprint yet effective Connectionist Temporal Classification based keyword spotting (CTC-KWS) systems. They a…
A Survey on Speech Large Language Models for Understanding
Jing Peng, Yucheng Wang, Bohan Li +9
Speech understanding is essential for interpreting the diverse forms of information embedded in spoken language, including linguistic, paralinguistic, and non-linguistic cues that…
Text-aware Speech Separation for Multi-talker Keyword Spotting
Haoyu Li, Baochen Yang, Yu Xi +4
For noisy environments, ensuring the robustness of keyword spotting (KWS) systems is essential. While much research has focused on noisy KWS, less attention has been paid to multi-…
TDT-KWS: Fast And Accurate Keyword Spotting Using Token-and-duration Transducer
Yu Xi, Hao Li, Baochen Yang +3
Designing an efficient keyword spotting (KWS) system that delivers exceptional performance on resource-constrained edge devices has long been a subject of significant attention. Ex…