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researcher

Ting He

9 papers hereh-index 41.2k citations7 works total

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

author position
  • middle author7

Across the 7 of 9 papers where every author was matched, so the position is known.

fields
  • eess.AS4
  • cs.CL2
  • cs.SD2
  • cs.AI1
same name
  • Ting He — 29 papers, h 32
  • Ting He — 7 papers, h 2
  • Ting He — 3 papers, h 2
  • Ting He — 1 paper, h 3
  • Ting He — 1 paper, h 4
  • Ting He — 1 paper, h 2

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
20242026
most citedQwen2.5-Omni Technical Report

12 citations · 24 across the 8 of their papers we have counts for

collaborators
Showing eess.ASShow all

4 papers · 1 filter

eess.AS2026

From Script to Drama: An Agentic Framework for Controllable Multi-Speaker Dialogue TTS

Kangxiang Xia, Xinfa Zhu, HangRui Hu +8

Multi-speaker dialogue TTS requires natural speech generation, consistent speaker identity, coherent cross-turn transitions, and fine-grained control of expressive attributes such…

eess.AS2026

Interactive TTS: Dynamic Speaking Style Adaptation for Expressive Speech Synthesis

Wenjie Tian, Kangxiang Xia, Jingbin Hu +7

Dynamic speaking style adaptation in multi-turn multimodal interaction remains a major challenge for text-to-speech (TTS) systems. Existing context-aware TTS (CTTS) methods typical…

eess.AS2026

DiaScriber: A Speech LLM for Joint Diarization and Transcription in Multi-Speaker Scenarios

Bingshen Mu, Xian Shi, Xiong Wang +6

Multi-speaker automatic speech recognition (MSASR) aims to jointly predict content transcriptions, speaker identities, and timestamps, thereby addressing the key question of "who s…

eess.AS2026

Qwen-Audio-VAE Technical Report

Ziyue Jiang, Dake Guo, Zekai Zhang +11

We introduce \textbf{Qwen-Audio-VAE}, a suite of low-bitrate, fast-encoding continuous audio autoencoders designed for scalable general audio generation. The model is built around…

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