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In the field of Human Computer Interaction (HCI), human emotion recognition from speech signal is evolving as a recent research area. Speech is the most common way for communication among human beings. Speech consists of sentences, which can be further segregated into words. Words consist of phonemes which are considered to be the primary voice construction elements. This paper presents a classification...
This paper explores the Linear Prediction (LP) residual of speech signal for characterizing the basic emotions. The emotions used in this study are anger, compassion, disgust, fear, happy, neutral, sarcastic and surprise. LP residual is derived by inverse filtering of the speech signal, and the process is known as LP analysis. LP residual mainly contains higher order relations among the samples. For...
Emotional speech plays an important role for conveying the desired message. Emotions are manifested in speech signal at all the levels, in particular they are significant at suprasegmental level (i.e., prosodic level). In this paper four emotions are characterized (anger, compassion, happy and neutral) using the prosodic features such as duration, intonation (variation of pitch), and energy. The analysis...
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