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researcher

Chao Zhang

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL2
  • cs.SD1
  • eess.AS1
ORCID 0000-0002-7730-5131
same name
  • Chao Zhang — 22 papers, h 38
  • Chao Zhang — 19 papers, h 22
  • Chao Zhang — 13 papers, h 10
  • Chao Zhang — 13 papers, h 7
  • Chao Zhang — 12 papers, h 21
  • Chao Zhang — 11 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedSpeaker diarisation using 2D self-attentive combination of embeddings

2 citations · 2 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CL2022

Turn-Taking Prediction for Natural Conversational Speech

Shuo-yiin Chang, Bo Li, Tara N. Sainath +4

While a streaming voice assistant system has been used in many applications, this system typically focuses on unnatural, one-shot interactions assuming input from a single voice qu…

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…

cs.CL2019★ 2 cited

Speaker diarisation using 2D self-attentive combination of embeddings

Guangzhi Sun, Chao Zhang, Phil Woodland

Speaker diarisation systems often cluster audio segments using speaker embeddings such as i-vectors and d-vectors. Since different types of embeddings are often complementary, this…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.