ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2210.08520
  4. Cited By
A Policy-based Approach to the SpecAugment Method for Low Resource E2E
  ASR

A Policy-based Approach to the SpecAugment Method for Low Resource E2E ASR

16 October 2022
Rui Li
Guodong Ma
Dexin Zhao
Ranran Zeng
Xiaoyu Li
Haolin Huang
ArXivPDFHTML

Papers citing "A Policy-based Approach to the SpecAugment Method for Low Resource E2E ASR"

3 / 3 papers shown
Title
LAE-ST-MoE: Boosted Language-Aware Encoder Using Speech Translation
  Auxiliary Task for E2E Code-switching ASR
LAE-ST-MoE: Boosted Language-Aware Encoder Using Speech Translation Auxiliary Task for E2E Code-switching ASR
Guodong Ma
Wenxuan Wang
Yuke Li
Yuting Yang
Binbin Du
Haoran Fu
13
5
0
28 Sep 2023
Data Augmentation Approaches in Natural Language Processing: A Survey
Data Augmentation Approaches in Natural Language Processing: A Survey
Bohan Li
Yutai Hou
Wanxiang Che
119
269
0
05 Oct 2021
MixSpeech: Data Augmentation for Low-resource Automatic Speech
  Recognition
MixSpeech: Data Augmentation for Low-resource Automatic Speech Recognition
Linghui Meng
Jin Xu
Xu Tan
Jindong Wang
Tao Qin
Bo Xu
VLM
62
75
0
25 Feb 2021
1