1 citations · 1 across the 6 of their papers we have counts for
6 papers
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…
STTATTS: Unified Speech-To-Text And Text-To-Speech Model
Hawau Olamide Toyin, Hao Li, Hanan Aldarmaki
Speech recognition and speech synthesis models are typically trained separately, each with its own set of learning objectives, training data, and model parameters, resulting in two…
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…
Contrastive Learning With Audio Discrimination For Customizable Keyword Spotting In Continuous Speech
Yu Xi, Baochen Yang, Hao Li +2
Customizable keyword spotting (KWS) in continuous speech has attracted increasing attention due to its real-world application potential. While contrastive learning (CL) has been wi…