Weak-Supervised Dysarthria-Invariant Features for Spoken Language Understanding Using an Fhvae and Adversarial Training-Reference-Cited by-同舟云学术

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Weak-Supervised Dysarthria-Invariant Features for Spoken Language Understanding Using an Fhvae and Adversarial Training

Published:2023-01-09 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Spoken Language Technology Workshop (SLT)
language:
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Author:

Qi Jinzi¹,Van hamme Hugo¹

Affiliation:

1. KULeuven,Department Electrical Engineering-ESAT-PSI,Leuven,Belgium

Funder

KU Leuven Special Research Fund

Flemish Government under the “Onderzoeksprogramma Artificiele Intelligentie (AI)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10022052/10022330/10023085.pdf?arnumber=10023085

Reference26 articles.

1. Personalized adversarial data augmentation for dysarthric and elderly speech recognition;jin;ArXiv Preprint,2022

2. Adver-sarial data augmentation for disordered speech recognition;jin;ArXiv Preprint,2021

3. Unsupervised Representation Learning of Speech for Dialect Identification

4. Unsuper-vised learning of disentangled and interpretable repre-sentations from sequential data;hsu;Advances in Neu-ral Information Processing Systems,2017

5. Significance of data augmentation for improving cleft lip and palate speech recognition;sudro;2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC),2021

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Models and Approaches for Comprehension of Dysarthric Speech Using Natural Language Processing: Systematic Review;JMIR Rehabilitation and Assistive Technologies;2023-10-27

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