most citedSTTATTS: Unified Speech-To-Text And Text-To-Speech Model

1 citations · 1 across the 6 of their papers we have counts for

collaborators
Showing eess.ASShow all

5 papers · 1 filter

eess.AS2024

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…

eess.AS2024

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…

eess.AS2024

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-…

eess.AS2024

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…

eess.AS2024

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…