Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Shibani Hamsa"'
Publikováno v:
Information, Vol 14, Iss 4, p 236 (2023)
Modern developments in machine learning methodology have produced effective approaches to speech emotion recognition. The field of data mining is widely employed in numerous situations where it is possible to predict future outcomes by using the inpu
Externí odkaz:
https://doaj.org/article/5697725ca3234e7a91567023510a4f22
Publikováno v:
IEEE Access, Vol 9, Pp 87995-88010 (2021)
This work presents an approach for text-independent and speaker-independent emotion recognition from speech in real application situations such as noisy and stressful talking conditions. We have incorporated a new way for feature extraction, represen
Externí odkaz:
https://doaj.org/article/46d56012876e4a7eb47faa84bd61388e
Publikováno v:
IEEE Access, Vol 8, Pp 96994-97006 (2020)
This research aims to design and implement an artificial emotional intelligence system that is capable of identifying the unknown emotion of the speaker. To that end, we propose a novel framework for emotion recognition in the presence of noise and i
Externí odkaz:
https://doaj.org/article/c8cf42a1f09d46feb8b0af4cc4751830
Publikováno v:
IEEE Access, Vol 7, Pp 26777-26787 (2019)
This paper aims at recognizing emotions for a text-independent and speaker-independent emotion recognition system based on a novel classifier, which is a hybrid of a cascaded Gaussian mixture model and deep neural network (GMM-DNN). This hybrid class
Externí odkaz:
https://doaj.org/article/6bbc6355a0bd4fe3a22bf83b14cd4c39
Publikováno v:
2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME).
Publikováno v:
IEEE Access, Vol 8, Pp 96994-97006 (2020)
This research aims to design and implement an artificial emotional intelligence system that is capable of identifying the unknown emotion of the speaker. To that end, we propose a novel framework for emotion recognition in the presence of noise and i
Publikováno v:
SSRN Electronic Journal.
Publikováno v:
IEEE Access, Vol 7, Pp 26777-26787 (2019)
This paper aims at recognizing emotions for a text-independent and speaker-independent emotion recognition system based on a novel classifier, which is a hybrid of a cascaded Gaussian mixture model and deep neural network (GMM-DNN). This hybrid class
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030736880
SoCPaR
SoCPaR
Speech experiences different acoustic obstructions in normal environment, whereas numerous of the applications require a compelling way to partitioned the original dominant speech from the impedance, a perfect hearing framework ought to be able to is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3a3178e4329d99be0095d12ab0c402a3
https://doi.org/10.1007/978-3-030-73689-7_38
https://doi.org/10.1007/978-3-030-73689-7_38