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Liang Huang

22 papers hereh-index 161.2k citations37 works total

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

author position
  • first author1
  • middle author4
  • last author17

Across the 22 of 22 papers where every author was matched, so the position is known.

fields
  • cs.CL19
  • eess.AS3
same name
  • Liang Huang — 22 papers, h 32
  • Liang Huang — 12 papers, h 26
  • Liang Huang — 9 papers, h 4
  • Liang Huang — 7 papers, h 10
  • Liang Huang — 7 papers, h 21
  • Liang Huang — 5 papers, h 9

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
20172026
most citedMAM: Masked Acoustic Modeling for End-to-End Speech-to-Text Translation

14 citations · 50 across the 22 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.CL2021★ 9 cited

The Role of Phonetic Units in Speech Emotion Recognition

Jiahong Yuan, Xingyu Cai, Renjie Zheng +2

We propose a method for emotion recognition through emotiondependent speech recognition using Wav2vec 2.0. Our method achieved a significant improvement over most previously report…

cs.CL2021★ 1 cited

Decoupling recognition and transcription in Mandarin ASR

Jiahong Yuan, Xingyu Cai, Dongji Gao +3

Much of the recent literature on automatic speech recognition (ASR) is taking an end-to-end approach. Unlike English where the writing system is closely related to sound, Chinese c…

cs.CL2021

Direct Simultaneous Speech-to-Text Translation Assisted by Synchronized Streaming ASR

Junkun Chen, Mingbo Ma, Renjie Zheng +1

Simultaneous speech-to-text translation is widely useful in many scenarios. The conventional cascaded approach uses a pipeline of streaming ASR followed by simultaneous MT, but suf…

cs.CL2021★ 6 cited

Fused Acoustic and Text Encoding for Multimodal Bilingual Pretraining and Speech Translation

Renjie Zheng, Junkun Chen, Mingbo Ma +1

Recently, representation learning for text and speech has successfully improved many language related tasks. However, all existing methods suffer from two limitations: (a) they onl…

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