Speech Emotion Recognition using Deep Learning
Nithya Roopa S.1, Prabhakaran M2, Betty.P3
1Nithya Roopa S, Assistant Professor, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
2Prabhakaran M, PG Scholar, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
3Betty. P, Assistant Professor, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 12 December 2018 | Revised Manuscript received on 23 December 2018 | Manuscript Published on 09 January 2019 | PP: 247-250 | Volume-7 Issue-4S November 2018 | Retrieval Number: E1917017519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Emotion recognition is the part of speech recognition which is gaining more popularity and need for it increases enormously. Although there are methods to recognize emotion using machine learning techniques, this project attempts to use deep learning and image classification method to recognize emotion and classify the emotion according to the speech signals. Various datasets are investigated and explored for training emotion recognition model are explained in this paper. Some of the issues on database, existing methodologies are addressed in the paper. Inception Net is used for emotion recognition with the paper. Inception Net is used for emotion recognition with IEMOCAP datasets. Final accuracy of this emotion recognition model using Inception Net v3 Model is 35%(~).
Keywords: Speech Recognition; Emotion Recognition; Automatic Speech Recognition; Deep Learning; Image Recognition; Speech Technology; Signal Processing; Image Classification.
Scope of the Article: Deep Learning