Text-aware Speech Separation for Multi-talker Keyword Spotting

H Li, B Yang, Y **, L Yu, T Tan, H Li, K Yu - arxiv preprint arxiv …, 2024 - arxiv.org
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 …

Distil-DCCRN: A Small-footprint DCCRN Leveraging Feature-based Knowledge Distillation in Speech Enhancement

R Han, W Xu, Z Zhang, M Liu… - IEEE Signal Processing …, 2024 - ieeexplore.ieee.org
The deep complex convolution recurrent network (DCCRN) achieves excellent speech
enhancement performance by utilizing the audio spectrum's complex features. However, it …

Detecting Spoofed Noisy Speeches via Activation-Based Residual Blocks for Embedded Systems

J Zhan, S Peng, W Jiang, X Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Spoofed noisy speeches seriously threaten the speech-based embedded systems, such as
smartphones and intelligent assistants. Consequently, we present an anti-spoofing detection …

Vocal Tract Length Warped Features for Spoken Keyword Spotting

P Dwivedi, ZH Tan - arxiv preprint arxiv:2501.03523, 2025 - arxiv.org
In this paper, we propose several methods that incorporate vocal tract length (VTL) warped
features for spoken keyword spotting (KWS). The first method, VTL-independent KWS …

OPC-KWS: Optimizing Keyword Spotting with Path Retrieval Decoding and Contrastive Learning

J Li, X Liu, X Zhang - 2024 IEEE 14th International Symposium …, 2024 - ieeexplore.ieee.org
As voice interaction capabilities with smart devices advance and the demand for
personalized wake words increases, customized keyword spotting (KWS) has become …