EAMR: An Emotion-aware Music Recommender Method via Mel Spectrogram and Arousal-Valence Model-Reference-Cited by-同舟云学术

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EAMR: An Emotion-aware Music Recommender Method via Mel Spectrogram and Arousal-Valence Model

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML)
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Author:

Fu Zixun¹,Zhang Zhen²,Zheng Jie³,Lin Ke⁴,Li Duantengchuan⁵

Affiliation:

1. Central China Normal University,Faculty of Artificial Intelligence in Education,Wuhan,China

2. School of Sports Engineering and Information Technology, Wuhan Sports University,Wuhan,China

3. School of Mathematics and Statistics, Hubei University of Arts and Science,Xiangyang,China

4. Harbin Institute of Technology (Shenzhen),Department of Control Science and Engineering,Shenzhen,China

5. School of Computer Science, Wuhan University,Wuhan,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9969169/9968314/09969215.pdf?arnumber=9969215

Reference21 articles.

1. Joint Temporal Convolutional Networks and Adversarial Discriminative Domain Adaptation for EEG-Based Cross-Subject Emotion Recognition

2. Symbolic Music Generation Conditioned on Continuous-Valued Emotions

3. Personalized Music Recommendation Algorithm Based on Hybrid Collaborative Filtering Technology

4. Hybrid Collaborative Filtering-Based API Recommendation

5. Five-Factor Musical Preference Prediction for Solving New User Cold-Start Problem in Content-Based Music Recommender System

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