System for Prediction of Human Emotions and Depression level with Recommendation of Suitable Therapy

Abstract

In today’s competitive world, an individual needs to act smartly and take rapid steps to make his place in the competition. The ratio of the youngsters to that of the elder people is comparatively more and also they contribute towards the development of the society. This paper presents the methodology to extract emotion from the text at real time and add the expression to the textual contents during speech synthesis by using Corpus , emotion recognition module etc. Along with the emotions recognition from the human textual data the system will analyze the various human body signals such as blood pressure, EEG signals , vocal prosody to predict the level of depression so that suitable therapy can be suggested using Prediction algorithm. In text analysis, all emotional keywords and emotion modification words are manually defined. To understand the existence of test was carried out on set of textual sentences and preliminary rules written for 34 different emotions. These rules are used in an automated procedure that assigns emotional state values to words. These values are then used by speech synthesizer to add emotions to speech & input sentence. Pitch detection algorithm has been implemented for pitch recognition.