Features Extraction From Speech For Emotion Recognition. |
Author(s): |
| Er. Pragati Pal , M.H.Saboo Siddik College Of Engineering; Dalal Fatema , M.H.Saboo Siddik College Of Engineering; Neha Shaikh , M.H.Saboo Siddik College Of Engineering; Ozair Shaikh, M.H.Saboo Siddik College Of Engineering |
Keywords: |
| Emotion recognitio, feature extraction, feature matching, Mel Frequency Cepstral Coefficient(MFCC), Hidden Markov Model (HMM) |
Abstract |
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Emotions form a basis of analyzing what an individual is feeling or experiencing at any given point of time. Emotion recognition will thus help us evaluate the temperament of an individual. In this paper emotion recognition is carried out by extracting certain necessary features from speech. Thus speech is forming the basis of emotion recognition. Emotion recognition is divided into two parts: feature extraction and pattern matching. Here feature extraction is carried out using Mel Frequency Cepstral Coefficients (MFCC) and pattern matching is done using Hidden Markov Model (HMM). |
Other Details |
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Paper ID: IJSRDV4I21083 Published in: Volume : 4, Issue : 2 Publication Date: 01/05/2016 Page(s): 1641-1643 |
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