2 citations · 3 across the 4 of their papers we have counts for
4 papers
sVAD: A Robust, Low-Power, and Light-Weight Voice Activity Detection with Spiking Neural Networks
Qu Yang, Qianhui Liu, Nan Li +3
Speech applications are expected to be low-power and robust under noisy conditions. An effective Voice Activity Detection (VAD) front-end lowers the computational need. Spiking Neu…
Locate and Beamform: Two-dimensional Locating All-neural Beamformer for Multi-channel Speech Separation
Yanjie Fu, Meng Ge, Honglong Wang +7
Recently, stunning improvements on multi-channel speech separation have been achieved by neural beamformers when direction information is available. However, most of them neglect t…
speech and noise dual-stream spectrogram refine network with speech distortion loss for robust speech recognition
Haoyu Lu, Nan Li, Tongtong Song +4
In recent years, the joint training of speech enhancement front-end and automatic speech recognition (ASR) back-end has been widely used to improve the robustness of ASR systems. T…
Deep Spectro-temporal Artifacts for Detecting Synthesized Speech
Xiaohui Liu, Meng Liu, Lin Zhang +7
The Audio Deep Synthesis Detection (ADD) Challenge has been held to detect generated human-like speech. With our submitted system, this paper provides an overall assessment of trac…