2 citations · 4 across the 6 of their papers we have counts for
6 papers
LLM-Anchored Paralinguistic Enrichment for Alzheimer's Disease Detection
Xiao Wei, Yuqin Lin, Yaru Cao +6
Speech-based automatic detection of Alzheimer's disease (AD) provides a non-invasive and scalable approach to early cognitive screening. AD affects both lexical-semantic organizati…
Gated Multi-Graph Fusion via Graph Attention Networks for Alzheimer's Disease Detection
Jinyu Li, Xiao Wei, Bin Wen +5
Spontaneous speech is a vital non-invasive biomarker for Alzheimer's Disease (AD), yet many systems overlook non-linear structural disruptions and clinical heterogeneity in patholo…
Modeling and Estimation of Vocal Tract and Glottal Source Parameters Using ARMAX-LF Model
Kai Lia, Masato Akagia, Yongwei Lib +1
Modeling and estimation of the vocal tract and glottal source parameters of vowels from raw speech can be typically done by using the Auto-Regressive with eXogenous input (ARX) mod…
A Neural State-Space Model Approach to Efficient Speech Separation
Chen Chen, Chao-Han Huck Yang, Kai Li +3
In this work, we introduce S4M, a new efficient speech separation framework based on neural state-space models (SSM). Motivated by linear time-invariant systems for sequence modeli…
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…
On the Design and Training Strategies for RNN-based Online Neural Speech Separation Systems
Kai Li, Yi Luo
While the performance of offline neural speech separation systems has been greatly advanced by the recent development of novel neural network architectures, there is typically an i…