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Zhiyun Lu

University of Southern California

14 papers hereh-index 14533 citations20 works total

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

author position
  • first author8
  • middle author5
  • last author1

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • eess.AS4
  • cs.CL2
  • cs.SD2
  • cs.CV1
  • stat.ML1
affiliations
  • University of Southern California
same name
  • Zhiyun Lu — 7 papers, h 5
  • Zhiyun Lu — 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
20142023
most citedKernel Approximation Methods for Speech Recognition

42 citations · 123 across the 13 of their papers we have counts for

collaborators
Showing eess.ASShow all

4 papers · 1 filter

eess.AS2022★ 1 cited

Unsupervised Data Selection via Discrete Speech Representation for ASR

Zhiyun Lu, Yongqiang Wang, Yu Zhang +3

Self-supervised learning of speech representations has achieved impressive results in improving automatic speech recognition (ASR). In this paper, we show that data selection is im…

eess.AS2022

Improving the fusion of acoustic and text representations in RNN-T

Chao Zhang, Bo Li, Zhiyun Lu +2

The recurrent neural network transducer (RNN-T) has recently become the mainstream end-to-end approach for streaming automatic speech recognition (ASR). To estimate the output dist…

eess.AS2021★ 10 cited

Input Length Matters: Improving RNN-T and MWER Training for Long-form Telephony Speech Recognition

Zhiyun Lu, Yanwei Pan, Thibault Doutre +5

End-to-end models have achieved state-of-the-art results on several automatic speech recognition tasks. However, they perform poorly when evaluated on long-form data, e.g., minutes…

eess.AS2021★ 1 cited

Exploring Targeted Universal Adversarial Perturbations to End-to-end ASR Models

Zhiyun Lu, Wei Han, Yu Zhang +1

Although end-to-end automatic speech recognition (e2e ASR) models are widely deployed in many applications, there have been very few studies to understand models' robustness agains…

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