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Zheng Lian

4 papers hereh-index 433 citations8 works total

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.SD4
same name
  • Zheng Lian — 28 papers, h 28
  • Zheng Lian — 25 papers, h 8
  • Zheng Lian — 15 papers, h 12
  • Zheng Lian — 10 papers, h 7
  • Zheng Lian — 8 papers, h 4
  • Zheng Lian — 4 papers, h 4

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
20222026
most citedADD 2022: the First Audio Deep Synthesis Detection Challenge

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

cs.SD2026

The NVVSpeech Challenge 2026: Overview and Lessons for Speech Understanding and Generation with Nonverbal Vocalizations

Liumeng Xue, Yuang Cao, Jingbin Hu +12

Nonverbal vocalizations (NVVs), such as laughter and sighs, convey meaning alongside words. NVV-aware speech systems must recognize and generate these events while preserving lexic…

cs.SD2025

P2Mark: Plug-and-play Parameter-level Watermarking for Neural Speech Generation

Yong Ren, Jiangyan Yi, Tao Wang +7

Neural speech generation (NSG) has rapidly advanced as a key component of artificial intelligence-generated content, enabling the generation of high-quality, highly realistic speec…

cs.SD2025

ALLM4ADD: Unlocking the Capabilities of Audio Large Language Models for Audio Deepfake Detection

Hao Gu, Jiangyan Yi, Chenglong Wang +6

Audio deepfake detection (ADD) has grown increasingly important due to the rise of high-fidelity audio generative models and their potential for misuse. Given that audio large lang…

cs.SD2022★ 1 cited

ADD 2022: the First Audio Deep Synthesis Detection Challenge

Jiangyan Yi, Ruibo Fu, Jianhua Tao +17

Audio deepfake detection is an emerging topic, which was included in the ASVspoof 2021. However, the recent shared tasks have not covered many real-life and challenging scenarios.…

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