Prediction of Closed Quotient During Vocal Phonation using GRU-type Neural Network with Audio Signals-Reference-Cited by-同舟云学术

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Prediction of Closed Quotient During Vocal Phonation using GRU-type Neural Network with Audio Signals

Published:2024-06-30 Issue:2 Volume:22 Page:145-152
ISSN:2234-8883
Container-title:Journal of information and communication convergence engineering
language:en
Short-container-title:JICCE

Author:

Han Hyeonbin¹^ORCID,Lee Keun Young²^ORCID,Shin Seong-Yoon³^ORCID,Kim Yoseup⁴^ORCID,Jo Gwanghyun¹^ORCID,Park Jihoon⁵^ORCID,Kim Young-Min⁶^ORCID

Affiliation:

1. Department of Mathematical Data Science, Hanyang University ERICA, Ansan, Republic of Korea

2. Independent scholar, Republic of Korea

3. School of Computer Science and Engineering, Kunsan National University, Gunsan 54150, Republic of Korea

4. Digital Healthcare Research Center, Deltoid Inc., 186 Jagok-ro, Seoul, Republic of Korea

5. Division of Vocal Music, Nicedream Music Academy, 48 Eoun-ro, Daejeon, Republic of Korea

6. Digital Health Research Divisions, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea

Funder

Korea Institute of Oriental Medicine

Publisher

Korea Institute of Information and Communication Engineering

Link

https://pdf.medrang.co.kr/JICCE/2024/022/JICCE022-02-145.pdf

Reference31 articles.

1. Automatic classification of laryngeal mechanisms in singing based on the audio signal

2. Register

3. Vocalic context as a condition for nasal coda emergence: aerodynamic evidence

4. Predictive value of Electroglottography in voice disorders

5. Relationship Between the Electroglottographic Signal and Vocal Fold Contact Area

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