relation: https://khub.utp.edu.my/scholars/19085/
title: Emotion Prediction in Music Based on Artificial Intelligence Techniques
creator: Lin, Y.-J.
creator: Ding, S.Y.
creator: Lu, C.-K.
creator: Tang, T.B.
creator: Shen, J.-Y.
description: Music is often described as the "language of emotion,"and emotion prediction is important as it can impact future behavior. This paper proposes an audio-based emotion prediction model using a One-Dimensional Convolutional Neural Network (1D-CNN) approach, with Mel-Frequency Cepstral Coefficients (MFCCs) extracted as audio features. Preliminary results show an overall accuracy of 93, but the imbalanced dataset used may cause bias in the accuracy of each emotion. Further research is needed to investigate the classification of audio features and 1D-CNN layers. © 2023 IEEE.
date: 2023
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Lin, Y.-J. and Ding, S.Y. and Lu, C.-K. and Tang, T.B. and Shen, J.-Y.  (2023) Emotion Prediction in Music Based on Artificial Intelligence Techniques.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174920802&doi=10.1109%2fICCE-Taiwan58799.2023.10226902&partnerID=40&md5=b23cc77ba7b805f2f7344ab3587814a1
relation: 10.1109/ICCE-Taiwan58799.2023.10226902
identifier: 10.1109/ICCE-Taiwan58799.2023.10226902