Estimating Underlying Articulatory Targets of Thai Vowels by Using Deep Learning Based on Generating Synthetic Samples From a 3D Vocal Tract Model and Data Augmentation-Reference-Cited by-同舟云学术

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Estimating Underlying Articulatory Targets of Thai Vowels by Using Deep Learning Based on Generating Synthetic Samples From a 3D Vocal Tract Model and Data Augmentation

Published:2022 Issue: Volume:10 Page:41489-41502
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Lapthawan Thanat^ORCID,Prom-On Santitham^ORCID,Birkholz Peter^ORCID,Xu Yi^ORCID

Funder

Leverhulme Trust Research Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09755932.pdf?arnumber=9755932

Reference72 articles.

1. Using self-supervised learning can improve model robustness and uncertainty;hendrycks;arXiv 1906 12340,2019

2. Listen, attend and spell: A neural network for large vocabulary conversational speech recognition

3. Attention is all you need;vaswani;Proc Adv Neural Inf Process Syst,2017

4. Construction And Control Of A Three-Dimensional Vocal Tract Model

5. Acoustic-to-articulatory inversion using Particle Swarm Optimization

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. Formant Frequency Tuning of Three-Dimensional MRI-Based Vocal Tracts for the Finite Element Synthesis of Vowels;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024

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