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Shi Wang

13 papers hereh-index 5256 citations14 works total

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

author position
  • first author6
  • middle author6

Across the 12 of 13 papers where every author was matched, so the position is known.

fields
  • cs.SD6
  • cs.CL3
  • eess.AS3
  • cs.AI1
same name
  • Shi Wang — 13 papers, h 5
  • Shi Wang — 7 papers, h 23
  • Shi Wang — 6 papers, h 7
  • Shi Wang — 5 papers, h 5
  • Shi Wang — 4 papers, h 1
  • Shi Wang — 4 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
20222026
most citedHow to Learn a New Language? An Efficient Solution for Self-Supervised Learning Models Unseen Languages Adaption in Low-Resource Scenario

1 citations · 1 across the 12 of their papers we have counts for

collaborators
Showing 2024 · cs.SDShow all

3 papers · 2 filters

cs.SD2024

Fusion of Discrete Representations and Self-Augmented Representations for Multilingual Automatic Speech Recognition

Shih-heng Wang, Jiatong Shi, Chien-yu Huang +2

Self-supervised learning (SSL) models have shown exceptional capabilities across various speech-processing tasks. Continuous SSL representations are effective but suffer from high…

cs.SD2024★ 1 cited

How to Learn a New Language? An Efficient Solution for Self-Supervised Learning Models Unseen Languages Adaption in Low-Resource Scenario

Shih-Heng Wang, Zih-Ching Chen, Jiatong Shi +6

The utilization of speech Self-Supervised Learning (SSL) models achieves impressive performance on Automatic Speech Recognition (ASR). However, in low-resource language ASR, they e…

cs.SD2024

ML-SUPERB 2.0: Benchmarking Multilingual Speech Models Across Modeling Constraints, Languages, and Datasets

Jiatong Shi, Shih-Heng Wang, William Chen +8

ML-SUPERB evaluates self-supervised learning (SSL) models on the tasks of language identification and automatic speech recognition (ASR). This benchmark treats the models as featur…

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