Automated Speech Emotion Recognition App Development on Smart Phones using Cloud Computing
Journal Title: International Journal of engineering Research and Applications - Year 2018, Vol 8, Issue 5
Abstract
Speech Emotion Recognition (SER) has become a major endeavor in Human-Computer Interaction (HCI) and speech processing. Accurate SER is essential for many applications, such as assessingcustomer satisfaction with the quality of services and detecting/assessing the emotional state of children in care. The large number of studiespublished on SER reflects the demand for its use. In thispaper, the proposed system presents a novelmethod of speech recognition based on the cloud model, in combination with the traditional speech emotion system. The process of predictingemotionsfrom speech emotion audio files containsseveral stages. The first stage of this system is the pre-processing stage, whichisapplied by detecting the speech in an audio file and thenreducing the noise. The second stage involvesextractingfeaturesfrom speech emotion files using the Melfrequency cepstral coefficient (MFCC) feature extraction algorithms. This generates the training and testingdatasetsthatcontain the emotions of Anger, Disgust, Fear, Happiness, Neutral, Sadness, and Surprise. Support Vector Machine (SVM) classifiers are thenused for the classification stage in order to predict the emotion. In addition, a Confusion Matrix (CM) technique isused to evaluate the performance of theseclassifiers. The proposed system istested on SAVEEand RMLdatabases and achieved a prediction rate of 95.3%
Authors and Affiliations
Humaid Alshamsi, Veton Kepuska, Hazza Alshamisi
Keywords
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- EP ID EP394198
- DOI 10.9790/9622-0805027177.
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