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This paper presents the analysis of affective speech of human for fatigue detection. Experimental results revealed that, there is a dependence of fatigue on human voice [3]. If a person is carrying fatigue or feeling depressed, then it is clearly reflected from his speech. Current research work on fatigue detection is based on normal human speech. This paper analyses the advantages of affective speech for precise determination of the state of fatigue. The analysis is carried out on the basis of various features such as fundamental frequency, formant frequencies, cepstrum, short-time energy etc.

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Energy-in-Motion is symbol of living hoods. This Energy-in-Motion is also knows as emotion. Digitization and Globalization change our traditional ways of living .This change are not only in physical but also physiological and hence , new generation is in a dilemma of unfit and unequipped also this has not a mental and physical strength to face and handle the emotional phases in for example stress or negative emotion. Now everyone is a part of race of success, from day one of school students enters in a world of in competition and stress. From the Kids to the youth are in stress of examination. Kids are missing there childhood. To bring their original age on their face is a need of understanding, Communication between the parents, teachers and friends. Right actions at can pull out them from the stress.. Hence researchers are working with this area of stress management. For our research work we simply tried to build a system 'Emotion Analysis using Rule base system.' Which can help to detect and classify the emotions?

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