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In the past decade a lot of research has gone into Automatic Speech Emotion Recognition(SER). The primary objective of SER is to improve man-machine interface. It can also be used to monitor the psycho physiological state of a person in lie detectors. In recent time, speech emotion recognition also find its applications in medicine and forensics. In this(More)
This paper aims at developing a Speaker Emotion Recognition (SER) system to recognize seven different emotions namely anger, boredom, fear, disgust, happiness, neutral and sadness with a generalized feature set in real-time. Continuous HMM and LIBSVM classifiers are considered in this paper. The choice of LIBSVM classifier provides better recognition rates(More)
Lexical chains are defined as clusters of semantically related words. The Lexical chaining architecture integrates domain dependent statistical word associations into the chaining process. The statistical word associations represent an additional type of lexical cohesive relationship that is not found in WordNet. The architecture also recognizes the gloss(More)
Emotion recognition and synthesis plays a crucial role in Human-computer interface. In this paper, we propose a multi style emotion recognition algorithm using time frequency (pH) and phase delay of a speech signal. Most of the work done so far on emotion recognition using spectral features mainly focuses on magnitude of the signal. Phase delay has been(More)
With ever increasing number of documents on web and other repositories, the task of organizing and categorizing these documents to the diverse need of the user by manual means is a complicated job, hence a machine learning technique named clustering is very useful. Text documents are clustered by pair wise similarity of documents with similarity measures(More)
Speech is one of the most popular modalities for emotion recognition. This work uses Mel and Bark scale dependent perceptual auditory features for recognizing seven emotions from Berlin speech corpus. A combination of Mel Frequency Cepstral Coefficients (MFCC's), Perceptual Linear Predictive Cepstrum (PLPC), Mel Frequency Perceptual Linear Predictive(More)
The paper deals with affective computing to improve the performance of Human-Machine interaction. The focus of this work is to detect affective state of a human using speech processing techniques primarily intended for call centre applications. Limited work is reported till date on affect detection using phase derived features. A unique combination of Group(More)
Emotion recognition from speech helps us in improving the effectiveness of human-machine interaction. This paper presents a method to identify suitable features in DWT domain and improve good accuracy. In this work, 7 emotions (Berlin Database) are recognized using Support Vector Machine (SVM) classifier. Entropy of Teager Energy operated Discrete Wavelet(More)
A MANET is a self configuring infrastructure less networks. It is usually connected by wireless. Each device in a MANET is independently to move in any direction. To maintain neighbor position the geographic location coordinates of the node is a famous method used by most geographic routing protocol for the purpose of periodic broadcasting of beacon(More)
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