Speech Emotion Recognition using Threshold Fusion for Enhancing Audio Sensitivity-Reference-Cited by-同舟云学术

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Speech Emotion Recognition using Threshold Fusion for Enhancing Audio Sensitivity

Published:2023-12-06 Issue: Volume: Page:
ISSN:
Container-title:ACM Multimedia Asia Workshops
language:
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Author:

Luo Zhaojie¹^ORCID,Christiansson Stefan²^ORCID,Ladóczki Bence³^ORCID,Komatani Kazunori¹^ORCID

Affiliation:

1. SANKEN, Osaka University, JP

2. KTH Royal Institute of Technology, SE

3. ELKH-BME Information Systems Research Group, Budapest University of Technology and Economics, HU

Funder

JSPS KAKENHI

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3611380.3628557

Reference33 articles.

1. Optuna

2. Rémi Bardenet , Mátyás Brendel , Balázs Kégl , and Michele Sebag . 2013 . Collaborative hyperparameter tuning . In International conference on machine learning. PMLR, 199–207 . Rémi Bardenet, Mátyás Brendel, Balázs Kégl, and Michele Sebag. 2013. Collaborative hyperparameter tuning. In International conference on machine learning. PMLR, 199–207.

3. James Bergstra , Rémi Bardenet , Yoshua Bengio , and Balázs Kégl . 2011. Algorithms for hyper-parameter optimization. Advances in neural information processing systems 24 ( 2011 ). James Bergstra, Rémi Bardenet, Yoshua Bengio, and Balázs Kégl. 2011. Algorithms for hyper-parameter optimization. Advances in neural information processing systems 24 (2011).

4. Calculation of a constant Q spectral transform

5. IEMOCAP: interactive emotional dyadic motion capture database

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