In new era of technology, machines can be given emotional intelligence. GDER system is such a system that provides fast response and, therefore, can be in events that require immediate application. For safety and security applications, where recognition of dangerous events is must in critical areas, such as railway stations and airports, the GDER system will recognize fear detected by several Smartphone users in the same zone to automatically monitor the whole area. GDER system can raise a huge alert of privacy and security issues. The CBI and law enforcement agencies can user the GDER system to identify possible suspects. This GDER system can be used beyond the examination and interpretation of voice. This new generation application is able to detect gender and recognize emotions of humans through voice. This system can be incorporated in psychological applications as well where mental and emotional state of the patient is to be understood.
The speech signal is in the form of analog signal. The speech is recorded and converted to digital form.
The system then accepts the speech input file for further processing.
The inputs strictly needs to be in the form of digital signal.
In the growing era of technology, the need for improved human-computer interaction
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First we will train the SVM classifiers. The SVM classifier for gender detection is trained by giving different speech inputs in order to classify the user as ”Male” or ”Female”. Then the SVM classifier for emotion recognition is trained by giving some inputs of different emotional states. The process of SVM training contains labelling of extracted features and training SVM. In the training process, the extracted features are assigned to a class label. The SVM is trained according to this labelled feature. The SVM kernel functions are used in the training process of