6 citations · 15 across the 15 of their papers we have counts for
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Selective State Space Model for Monaural Speech Enhancement
Moran Chen, Qiquan Zhang, Mingjiang Wang +4
Voice user interfaces (VUIs) have facilitated the efficient interactions between humans and machines through spoken commands. Since real-word acoustic scenes are complex, speech en…
SAV-SE: Scene-aware Audio-Visual Speech Enhancement with Selective State Space Model
Xinyuan Qian, Jiaran Gao, Yaodan Zhang +4
Speech enhancement plays an essential role in various applications, and the integration of visual information has been demonstrated to bring substantial advantages. However, the ma…
Mamba in Speech: Towards an Alternative to Self-Attention
Xiangyu Zhang, Qiquan Zhang, Hexin Liu +6
Transformer and its derivatives have achieved success in diverse tasks across computer vision, natural language processing, and speech processing. To reduce the complexity of compu…
Aligning Speech to Languages to Enhance Code-switching Speech Recognition
Hexin Liu, Xiangyu Zhang, Haoyang Zhang +4
Code-switching (CS) refers to the switching of languages within a speech signal and results in language confusion for automatic speech recognition (ASR). To address language confus…
When LLMs Meets Acoustic Landmarks: An Efficient Approach to Integrate Speech into Large Language Models for Depression Detection
Xiangyu Zhang, Hexin Liu, Kaishuai Xu +4
Depression is a critical concern in global mental health, prompting extensive research into AI-based detection methods. Among various AI technologies, Large Language Models (LLMs)…
Speaking in Wavelet Domain: A Simple and Efficient Approach to Speed up Speech Diffusion Model
Xiangyu Zhang, Daijiao Liu, Hexin Liu +5
Recently, Denoising Diffusion Probabilistic Models (DDPMs) have attained leading performances across a diverse range of generative tasks. However, in the field of speech synthesis,…