6 citations · 18 across the 22 of their papers we have counts for
8 papers · 1 filter
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…
Rethinking Mamba in Speech Processing by Self-Supervised Models
Xiangyu Zhang, Jianbo Ma, Mostafa Shahin +2
The Mamba-based model has demonstrated outstanding performance across tasks in computer vision, natural language processing, and speech processing. However, in the realm of speech…
Auto-Landmark: Acoustic Landmark Dataset and Open-Source Toolkit for Landmark Extraction
Xiangyu Zhang, Daijiao Liu, Tianyi Xiao +5
In the speech signal, acoustic landmarks identify times when the acoustic manifestations of the linguistically motivated distinctive features are most salient. Acoustic landmarks h…
Binaural Selective Attention Model for Target Speaker Extraction
Hanyu Meng, Qiquan Zhang, Xiangyu Zhang +2
The remarkable ability of humans to selectively focus on a target speaker in cocktail party scenarios is facilitated by binaural audio processing. In this paper, we present a binau…
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,…