Current Result Document :
| 한글제목(Korean Title) |
딥네트워크 기반 음성 감정인식 기술 동향 |
| 영문제목(English Title) |
Speech Emotion Recognition Based on Deep Networks: A Review |
| 저자(Author) |
무스타킴
권순일
Mustaqeem
Soonil Kwon
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| 원문수록처(Citation) |
VOL 28 NO. 01 PP. 0331 ~ 0334 (2021. 05) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
In the latest eras, there has been a significant amount of development and research is done on the sage of Deep Learning (DL) for speech emotion recognition (SER) based on Convolutional Neural Network (CNN). These techniques are usually focused on utilizing CNN for an application associated with emotion recognition. Moreover, numerous mechanisms are deliberated that is based on deep learning, meanwhile, it’s important in the SER-based human-computer interaction (HCI) applications. Associating with other methods, the methods created by DL are presenting quite motivating results in many fields including automatic speech recognition. Hence, it appeals to a lot of studies and investigations. In this article, a review with evaluations is illustrated on the improvements that happened in the SER domain though likewise arguing the existing studies that are existence SER based on DL and CNN methods.
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| 키워드(Keyword) |
Affective computing
deep learning
convolutional neural networks
machine learning
speech recognition
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| 파일첨부 |
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