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Chao Zhang

12 papers hereh-index 13944 citations31 works total

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

author position
  • first author2
  • middle author9

Across the 11 of 12 papers where every author was matched, so the position is known.

fields
  • eess.AS6
  • cs.CL3
  • cs.AI1
  • cs.LG1
  • cs.SD1
same name
  • Chao Zhang — 38 papers, h 21
  • Chao Zhang — 38 papers, h 38
  • Chao Zhang — 23 papers, h 22
  • Chao Zhang — 23 papers, h 7
  • Chao Zhang — 23 papers, h 11
  • Chao Zhang — 21 papers, h 14

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

activity
20192022
most citedAdapting GPT, GPT-2 and BERT Language Models for Speech Recognition

5 citations · 7 across the 6 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

eess.AS2020

Improving Prosody Modelling with Cross-Utterance BERT Embeddings for End-to-end Speech Synthesis

Guanghui Xu, Wei Song, Zhengchen Zhang +3

Despite prosody is related to the linguistic information up to the discourse structure, most text-to-speech (TTS) systems only take into account that within each sentence, which ma…

cs.CL2020

Emotion recognition by fusing time synchronous and time asynchronous representations

Wen Wu, Chao Zhang, Philip C. Woodland

In this paper, a novel two-branch neural network model structure is proposed for multimodal emotion recognition, which consists of a time synchronous branch (TSB) and a time asynch…

cs.SD2020

Combination of Deep Speaker Embeddings for Diarisation

Guangzhi Sun, Chao Zhang, Phil Woodland

Significant progress has recently been made in speaker diarisation after the introduction of d-vectors as speaker embeddings extracted from neural network (NN) speaker classifiers…

eess.AS2020

Neural Kalman Filtering for Speech Enhancement

Wei Xue, Gang Quan, Chao Zhang +3

Statistical signal processing based speech enhancement methods adopt expert knowledge to design the statistical models and linear filters, which is complementary to the deep neural…

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