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Exploiting semi-supervised training through a dropout regularization in end-to-end speech recognition

Exploiting semi-supervised training through a dropout regularization in end-to-end speech recognition

S. Dey
P. Motlícek
Trung H. Bui
Franck Dernoncourt
ArXiv (abs)PDFHTML

Papers citing "Exploiting semi-supervised training through a dropout regularization in end-to-end speech recognition"

7 / 7 papers shown
Title
Multiple-hypothesis RNN-T Loss for Unsupervised Fine-tuning and Self-training of Neural Transducer
Multiple-hypothesis RNN-T Loss for Unsupervised Fine-tuning and Self-training of Neural Transducer
Cong-Thanh Do
Mohan Li
R. Doddipatla
55
3
0
29 Jul 2022
ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale
ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale
Gopinath Chennupati
Milind Rao
Gurpreet Chadha
Aaron Eakin
A. Raju
...
Andrew Oberlin
Buddha Nandanoor
Prahalad Venkataramanan
Zheng Wu
Pankaj Sitpure
CLL
97
8
0
19 Jul 2022
Magic dust for cross-lingual adaptation of monolingual wav2vec-2.0
Magic dust for cross-lingual adaptation of monolingual wav2vec-2.0
Sameer Khurana
Antoine Laurent
James R. Glass
VLM
119
18
0
07 Oct 2021
Low Resource German ASR with Untranscribed Data Spoken by Non-native Children -- INTERSPEECH 2021 Shared Task SPAPL System
Low Resource German ASR with Untranscribed Data Spoken by Non-native Children -- INTERSPEECH 2021 Shared Task SPAPL System
Jinhan Wang
Yunzheng Zhu
Ruchao Fan
Wei Chu
Abeer Alwan
69
8
0
18 Jun 2021
Contextual Semi-Supervised Learning: An Approach To Leverage Air-Surveillance and Untranscribed ATC Data in ASR Systems
Contextual Semi-Supervised Learning: An Approach To Leverage Air-Surveillance and Untranscribed ATC Data in ASR Systems
Juan Pablo Zuluaga
Iuliia Nigmatulina
Amrutha Prasad
P. Motlícek
Karel Veselý
M. Kocour
Igor Szöke
130
27
0
08 Apr 2021
Semi-Supervised Learning with Data Augmentation for End-to-End ASR
Semi-Supervised Learning with Data Augmentation for End-to-End ASR
F. Weninger
F. Mana
R. Gemello
Jesús Andrés-Ferrer
P. Zhan
91
30
0
27 Jul 2020
Deep Contextualized Acoustic Representations For Semi-Supervised Speech Recognition
Deep Contextualized Acoustic Representations For Semi-Supervised Speech Recognition
Shaoshi Ling
Yuzong Liu
Julian Salazar
Katrin Kirchhoff
SSL
86
139
0
03 Dec 2019

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