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In speech communication, humans are able to perceive not only the acoustic features but also the articulation state from speech sounds. Some specific articulation configurations can carry certain non-linguistic information such as emotion. However, the relation between articulation and acoustic features is still not clear. To clarify such a relation, we analyzed speech data from the emotions of cold...
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...
To study effective speech features which can represent different emotion styles in infant voice, nonlinear features based on Teager Energy Operator are investigated. Neutral state and 4 emotional states (i.e. happiness, impatience, anger and fear) are classified from the infant voice database. MFCC extraction and HMM-based emotion classification are used as baseline system to evaluate the emotional...
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