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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM17741

Deep Learning for the Recognition of Human Speech

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM17741

Volume:

7 |

2 |

Feb 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

KAS

Kandula Akhil Sai

GLS

G. Lakshmi Sowjanya

KG

Kamineni Gopal

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Abstract

Humans primarily communicate through speech, and language is their main means of doing so. Emotion is crucial to social connection. Knowing how to recognise the emotions in a speech is important and challenging given that we are dealing with human-machine interaction. Depending on the mood a person is going through, they will express themselves differently. When someone expresses their emotions, each one has a distinctive energy, pitch, and tone fluctuation that is categorised according to the situation. The identification of spoken emotions is thus a future goal for computer vision. The objective of our project is to develop intelligent speech that utilises a convolutional neural network to recognise emotions. which uses a variety of modules for emotion recognition and classifier.

KEYWORDS

Human speech Emotion recognition of speech GMM Mel-Frequency-Cepstrum Coefficient (MFCC) linear prediction Cepstral coefficients (LPCC) (LSTM)

Cite This Article

Kandula Akhil Sai, G. Lakshmi Sowjanya, Kamineni Gopal, "Deep Learning for the Recognition of Human Speech," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 2, Feb 2023. https://doi.org/10.55041/IJSREM17741

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Publication Date

2/14/2023

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Double-Blind Peer Review

Review Rounds: 2

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