Volume & Issue no: Volume 8, Issue 3, May - June 2019
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Title: |
Speech Emotion Recognition using Convolutional Neural Networks |
Author Name: |
Dr. B.S. Daga, Glaston Dsouza, Aadesh Bassi, Lionel Lobo |
Abstract: |
Abstract: In today’s world, Human machine interaction
are used nowadays in many applications. Speech is one of
the medium of interaction. Detection of emotion from
speech is a main challenge. Communicating with
emotions is more affective compared otherwise, since they
can be expressed and identified in a better way through
facial expressions, speech, gestures etc. If machines
understand the emotional content they will start behaving
in a friendlier way.
Recognition of emotion is always a difficult problem,
particularly if the recognition of emotion is done by using
speech signal. Significant research has been done on
emotion recognition using speech signal. The primary
challenges are choosing the emotion recognition corpora
i.e. database, identification of different features related to
speech and selecting an appropriate choice of
classification model.
Speech Emotion problem is categorized as:
1) Feature extraction from speech: For this MFCC is
used. We use 13 MFCC with 13 velocity and 13
acceleration component as features.
2) Feature classification: The features from MFCC are
passed to CNN layer where the classification of above
features is done.
3) Emotion detection: Depending on the output from
CNN the corresponding emotion is detected i.e. happy,
sad, angry, calm, fear.
Keywords: CNN-Convolution neural network, MFCC-Mel
Frequency Cepstral Coefficient, SAVEE, RAVDESS. |
Cite this article: |
Dr. B.S. Daga, Glaston Dsouza, Aadesh Bassi, Lionel Lobo , "
Speech Emotion Recognition using Convolutional Neural Networks" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) ,
Volume 8, Issue 3, May - June 2019 , pp.
008-013 , ISSN 2278-6856.
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