activity
20162025
most citedSelf-supervised representations in speech-based depression detection

34 citations · 131 across the 42 of their papers we have counts for

collaborators
Showing 2022Show all

8 papers · 1 filter

cs.CL2022★ 8 cited

Distribution-based Emotion Recognition in Conversation

Wen Wu, Chao Zhang, Philip C. Woodland

Automatic emotion recognition in conversation (ERC) is crucial for emotion-aware conversational artificial intelligence. This paper proposes a distribution-based framework that for…

cs.CL2022

Biased Self-supervised learning for ASR

Florian L. Kreyssig, Yangyang Shi, Jinxi Guo +3

Self-supervised learning via masked prediction pre-training (MPPT) has shown impressive performance on a range of speech-processing tasks. This paper proposes a method to bias self…

cs.CL2022

End-to-end Spoken Language Understanding with Tree-constrained Pointer Generator

Guangzhi Sun, Chao Zhang, Philip C. Woodland

End-to-end spoken language understanding (SLU) suffers from the long-tail word problem. This paper exploits contextual biasing, a technique to improve the speech recognition of rar…

cs.SD2022

Spectral Clustering-aware Learning of Embeddings for Speaker Diarisation

Evonne P. C. Lee, Guangzhi Sun, Chao Zhang +1

In speaker diarisation, speaker embedding extraction models often suffer from the mismatch between their training loss functions and the speaker clustering method. In this paper, w…

eess.AS2022

Tandem Multitask Training of Speaker Diarisation and Speech Recognition for Meeting Transcription

Xianrui Zheng, Chao Zhang, Philip C. Woodland

Self-supervised-learning-based pre-trained models for speech data, such as Wav2Vec 2.0 (W2V2), have become the backbone of many speech tasks. In this paper, to achieve speaker diar…

cs.SD2022

Tree-constrained Pointer Generator with Graph Neural Network Encodings for Contextual Speech Recognition

Guangzhi Sun, Chao Zhang, Philip C. Woodland

Incorporating biasing words obtained as contextual knowledge is critical for many automatic speech recognition (ASR) applications. This paper proposes the use of graph neural netwo…