Using Self-learning Representations for Objective Assessment of Patient Voice in Dysphonia-Reference-Cited by-同舟云学术

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Using Self-learning Representations for Objective Assessment of Patient Voice in Dysphonia

Published:2022-11-07 Issue: Volume: Page:
ISSN:
Container-title:2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)
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Author:

Dang Shaoxiang¹,Matsumoto Tetsuya¹,Takeuchi Yoshinori²,Kudo Hiroaki¹,Tsuboi Takashi³,Tanaka Yasuhiro⁴,Katsuno Masahisa³

Affiliation:

1. Graduate School of Informatics, Nagoya University,Nagoya,Japan

2. School of Informatics, Daido University,Nagoya,Japan

3. Nagoya University Graduate School of Medicine,Department of Neurology,Nagoya,Japan

4. Aichi Gakuin University,Faculty of Psychological and Physical Science,Department of Health Science,Nissin,Japan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9979726/9979808/09980071.pdf?arnumber=9980071

Reference21 articles.

1. Pathological Voice Classification Using Deep Learning

2. Automatic Estimation of Pathological Voice Quality Based on Recurrent Neural Network Using Amplitude and Phase Spectrogram

3. MBNET: MOS Prediction for Synthesized Speech with Mean-Bias Network

4. LDNet: Unified Listener Dependent Modeling in MOS Prediction for Synthetic Speech

5. Energy-efficient Metro Train Operation Considering the Regenerative Energy: A Discrete Differential Dynamic Programming Approach

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