Classification and Analysis of Emotion from Speech Signals

Recognizing emotion from speech has become one the active research themes in speech processing and in applications based on human-computer interaction. This paper conducts an experimental study on recognizing emotions from human speech. The emotions considered for the experiments include neutral, anger, joy and sadness. The distinguish ability of emotional features in speech were studied first followed by emotion classification performed on a custom dataset. The classification was performed for different classifiers. One of the main feature attribute considered in the prepared dataset was the peak-to-peak distance obtained from the graphical representation of the speech signals. Emotion is defined as the positive or negative state of a person’s mind which is related with a pattern of physiological activities. Emotions describe the mental state of a person. Sometimes in many applications such as military & civilian applications , in police department , its necessary to access whether a speaker is talking genuine or not and becoming increasingly important in security systems. So this project deals with the conditions like , if the speaker is involved in a stressful activity then the speech signal will be the significant indicator of the psychological stress. In this project speakers speech will be analysed depending on short time spectrum of vowels. For that we will have to take sample of some speech signals since the factors such as mood , emosion , physical characteristics are contained in the speech signal.