A feature selection model for speech emotion recognition using clustering-based population generation with hybrid of equilibrium optimizer and atom search optimization algorithm
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-021-11839-3.pdf
Reference81 articles.
1. Barros P, Weber C, Wermter S (2015) Emotional expression recognition with a cross-channel convolutional neural network for human-robot interaction. In: 2015 IEEE- RAS 15Th international conference on humanoid robots (Humanoids), IEEE, pp 582–587
2. Blum A, Mitchell T (1998) Combining labeled and unlabeled data with co-training. In: Proceedings of the eleventh annual conference on Computational learning theory, pp 92–100
3. Boigne J, Liyanage B, Östrem T (2020) Recognizing more emotions with less data using self-supervised transfer learning. arXiv:201105585
4. Bookstein A, Kulyukin VA, Raita T (2002) Generalized hamming distance. Inf Retr 5(4):353–375
5. Burkhardt F, Paeschke A, Rolfes M, Sendlmeier WF, Weiss B (2005) A database of german emotional speech. In: Ninth european conference on speech communication and technology
Cited by 15 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. EO-CNN: Equilibrium Optimization-Based hyperparameter tuning for enhanced pneumonia and COVID-19 detection using AlexNet and DarkNet19;Biocybernetics and Biomedical Engineering;2024-07
2. A novel two-way feature extraction technique using multiple acoustic and wavelets packets for deep learning based speech emotion recognition;Multimedia Tools and Applications;2024-06-17
3. Feature fusion: research on emotion recognition in English speech;International Journal of Speech Technology;2024-05-30
4. Comparative Performance Analysis of Metaheuristic Feature Selection Methods for Speech Emotion Recognition;Measurement Science Review;2024-04-01
5. A feature selection method based on the Golden Jackal-Grey Wolf Hybrid Optimization Algorithm;PLOS ONE;2024-01-02
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3