Daily Mental Health Monitoring from Speech: A Real-World Japanese Dataset and Multitask Learning Analysis-Reference-Cited by-同舟云学术

Daily Mental Health Monitoring from Speech: A Real-World Japanese Dataset and Multitask Learning Analysis

Published:2023-06-04 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Song Meishu¹,Triantafyllopoulos Andreas¹,Yang Zijiang¹,Takeuchi Hiroki²,Nakamura Toru³,Kishi Akifumi⁴,Ishizawa Tetsuro⁴,Yoshiuchi Kazuhiro⁴,Jing Xin¹,Karas Vincent¹,Zhao Zhonghao⁵,Qian Kun⁵,Hu Bin⁵,Schuller Björn W¹,Yamamoto Yoshiharu²

Affiliation:

1. University of Augsburg,Chair of Embedded Intelligence for Health Care and Wellbeing,Germany

2. University of Tokyo,Educational Physiology Laboratory, Graduate School of Education,Japan

3. Osaka University,Institute for Datability Science,Japan

4. The University of Tokyo,Graduate School of Medicine,Japan

5. Beijing Institute of Technology,School of Medical Technology,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10094559/10094560/10096884.pdf?arnumber=10096884

Reference30 articles.

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3. Evaluating the Impact of Voice Activity Detection on Speech Emotion Recognition for Autistic Children

4. An Early Study on Intelligent Analysis of Speech Under COVID-19: Severity, Sleep Quality, Fatigue, and Anxiety

5. Deep speaker conditioning for speech emotion recognition

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