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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...
The paper is focused on an experimental study on positive and negative emotion vocal recognition. After some considerations about the positive and negative emotions, the paper gives a short description of the three corpuses used in the work we have accomplished. The paper describes three sets of coefficients used, the statistic features used to generate the three sets of feature vectors and the two...
In this paper, prosodic analysis of speech segments is performed to recognise emotions. Speech signal is segmented into words and syllables. Energy and pitch parameters are extracted from utterances, words and syllables separately to develop emotion recognition models. Eight emotions (anger, disgust, fear, happy, neutral, sad, sarcastic and surprise) of simulated emotion speech corpus, IITKGP SESC...
This paper proposes epoch parameters extracted from LP (Linear Prediction) residual and zero frequency filtered speech signal for recognising the emotions present in speech. Instant of glottal closure within pitch period of LP residual is known as an 'epoch'. The significant excitation of vocal tract usually takes place at the instant of glottal closure. In this paper the epoch parameters namely strength...
We present novel methods for estimating spontaneously expressed emotions in speech. Three continuous-valued emotion primitives are used to describe emotions, namely valence, activation, and dominance. For the estimation of these primitives, support vector machines (SVMs) are used in their application for regression (support vector regression, SVR). Feature selection and parameter optimization are...
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