Abstract

The speech emotion recognition is a very interesting yet very challenging task of human computer interaction. In the recent years this topic has grabbed so much attention. In the field of speech emotion recognition many techniques have been utilized to extract emotions from signals , including many well- established speech analysis and classification techniques. In the traditional way of speech emotion recognition features are extracted from the speech signals and then the features are selected which is collectively know as selection module and then the emotions are recognized this is a very lengthy and time taking process. To understand the importance of Speech emotion & facial expression and how it is important for emotion detection. Emotion detection from our project has vast study for further future research and development. To build automatically speech and facial expression recognition has an effective emerging for developments. This project extends study and development on emotion detection with speech and facial expressions using Convolution Neural network (CNN). This task is done by detecting the facial actions per every unit of face measurements as a sub part of facial action coding system. This project offers light on utilization of CNN from a live video stream as an input. Using various machine learning libraries like tensor flow and many more. With this development it's advantageous to various domains such as medical engineering, technology, marketing etc.. Key words:- Emotion , Features , Facial expressions , Speech , Techniques , Technology.

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