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Chenglong Wang

23 papers hereh-index 191.5k citations34 works total

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

author position
  • first author4
  • middle author16
  • last author1

Across the 21 of 23 papers where every author was matched, so the position is known.

fields
  • cs.SD22
  • eess.AS1
same name
  • Chenglong Wang — 39 papers, h 10
  • Chenglong Wang — 10 papers, h 16
  • Chenglong Wang — 9 papers, h 5
  • Chenglong Wang — 8 papers, h 10
  • Chenglong Wang — 5 papers, h 10
  • Chenglong Wang — 5 papers, h 3

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
20212025
most citedContinual Learning for Fake Audio Detection

35 citations · 150 across the 23 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.SD2024

Region-Based Optimization in Continual Learning for Audio Deepfake Detection

Yujie Chen, Jiangyan Yi, Cunhang Fan +10

Rapid advancements in speech synthesis and voice conversion bring convenience but also new security risks, creating an urgent need for effective audio deepfake detection. Although…

cs.SD2024

Utilizing Speaker Profiles for Impersonation Audio Detection

Hao Gu, JiangYan Yi, Chenglong Wang +5

Fake audio detection is an emerging active topic. A growing number of literatures have aimed to detect fake utterance, which are mostly generated by Text-to-speech (TTS) or voice c…

eess.AS2024★ 2 cited

ADD 2023: Towards Audio Deepfake Detection and Analysis in the Wild

Jiangyan Yi, Chu Yuan Zhang, Jianhua Tao +5

The growing prominence of the field of audio deepfake detection is driven by its wide range of applications, notably in protecting the public from potential fraud and other malicio…

cs.SD2024★ 1 cited

RawBMamba: End-to-End Bidirectional State Space Model for Audio Deepfake Detection

Yujie Chen, Jiangyan Yi, Jun Xue +7

Fake artefacts for discriminating between bonafide and fake audio can exist in both short- and long-range segments. Therefore, combining local and global feature information can ef…

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