Current Result Document : 31 / 184
ÇѱÛÁ¦¸ñ(Korean Title) |
µö³×Æ®¿öÅ© ±â¹Ý À½¼º °¨Á¤ÀÎ½Ä ±â¼ú µ¿Çâ |
¿µ¹®Á¦¸ñ(English Title) |
Speech Emotion Recognition Based on Deep Networks: A Review |
ÀúÀÚ(Author) |
¹«½ºÅ¸Å´
±Ç¼øÀÏ
Mustaqeem
Soonil Kwon
|
¿ø¹®¼ö·Ïó(Citation) |
VOL 28 NO. 01 PP. 0331 ~ 0334 (2021. 05) |
Çѱ۳»¿ë (Korean Abstract) |
|
¿µ¹®³»¿ë (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.
|
Å°¿öµå(Keyword) |
Affective computing
deep learning
convolutional neural networks
machine learning
speech recognition
|
ÆÄÀÏ÷ºÎ |
PDF ´Ù¿î·Îµå
|