7 citations · 19 across the 7 of their papers we have counts for
7 papers
Quantifying Entrainment Evidence: A Comparison of Frequentist and Bayesian Approaches for Information Processing Pathway Maps
Kaibo Zhang, Ji Wu, Chao Zhang +1
Information Processing Pathway Maps (IPPMs) offer a scalable framework for formalizing the complex sequence of mathematical transformations applied to sensory stimuli. These maps c…
The 1st SpeechWellness Challenge: Detecting Suicide Risk Among Adolescents
Wen Wu, Ziyun Cui, Chang Lei +6
The 1st SpeechWellness Challenge (SW1) aims to advance methods for detecting current suicide risk in adolescents using speech analysis techniques. Suicide among adolescents is a cr…
Spontaneous Speech-Based Suicide Risk Detection Using Whisper and Large Language Models
Ziyun Cui, Chang Lei, Wen Wu +5
The early detection of suicide risk is important since it enables the intervention to prevent potential suicide attempts. This paper studies the automatic detection of suicide risk…
Bayesian Example Selection Improves In-Context Learning for Speech, Text, and Visual Modalities
Siyin Wang, Chao-Han Huck Yang, Ji Wu +1
Large language models (LLMs) can adapt to new tasks through in-context learning (ICL) based on a few examples presented in dialogue history without any model parameter update. Desp…
MAV: A Multimodal, Multigenre, and Multipurpose Audio-Visual Academic Lecture Dataset
Zhe Chen, Heyang Liu, Wenyi Yu +6
Publishing open-source academic video recordings is an emergent and prevalent approach to sharing knowledge online. Such videos carry rich multimodal information including speech,…
Transferring speech-generic and depression-specific knowledge for Alzheimer's disease detection
Ziyun Cui, Wen Wu, Wei-Qiang Zhang +2
The detection of Alzheimer's disease (AD) from spontaneous speech has attracted increasing attention while the sparsity of training data remains an important issue. This paper hand…
Can Whisper perform speech-based in-context learning?
Siyin Wang, Chao-Han Huck Yang, Ji Wu +1
This paper investigates the in-context learning abilities of the Whisper automatic speech recognition (ASR) models released by OpenAI. A novel speech-based in-context learning (SIC…