activity
20182025
most citedSelf-supervised representations in speech-based depression detection

34 citations · 91 across the 31 of their papers we have counts for

collaborators

42 papers

eess.AS2025

DNCASR: End-to-End Training for Speaker-Attributed ASR

Xianrui Zheng, Chao Zhang, Philip C. Woodland

This paper introduces DNCASR, a novel end-to-end trainable system designed for joint neural speaker clustering and automatic speech recognition (ASR), enabling speaker-attributed t…

eess.AS2024

MT2KD: Towards A General-Purpose Encoder for Speech, Speaker, and Audio Events

Xiaoyu Yang, Qiujia Li, Chao Zhang +1

With the advances in deep learning, the performance of end-to-end (E2E) single-task models for speech and audio processing has been constantly improving. However, it is still chall…

eess.AS2024

SOT Triggered Neural Clustering for Speaker Attributed ASR

Xianrui Zheng, Guangzhi Sun, Chao Zhang +1

This paper introduces a novel approach to speaker-attributed ASR transcription using a neural clustering method. With a parallel processing mechanism, diarisation and ASR can be ap…

cs.CL2024★ 1 cited

Confidence Estimation for Automatic Detection of Depression and Alzheimer's Disease Based on Clinical Interviews

Wen Wu, Chao Zhang, Philip C. Woodland

Speech-based automatic detection of Alzheimer's disease (AD) and depression has attracted increased attention. Confidence estimation is crucial for a trust-worthy automatic diagnos…

cs.LG2024★ 1 cited

An Improved Empirical Fisher Approximation for Natural Gradient Descent

Xiaodong Wu, Wenyi Yu, Chao Zhang +1

Approximate Natural Gradient Descent (NGD) methods are an important family of optimisers for deep learning models, which use approximate Fisher information matrices to pre-conditio…

eess.AS2024

1st Place Solution to Odyssey Emotion Recognition Challenge Task1: Tackling Class Imbalance Problem

Mingjie Chen, Hezhao Zhang, Yuanchao Li +11

Speech emotion recognition is a challenging classification task with natural emotional speech, especially when the distribution of emotion types is imbalanced in the training and t…