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Fundamental Frequency Extraction Method using Central Clipping and its Importance for the Classification of Emotional State

Keywords: Central clipping , DC offset , emotional state , features extraction , hamming smoothing window , homoscedasticity , pre-emphasis.

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The paper deals with a classification of emotional state. We implemented a method for extracting the fundamental speech signal frequency by means of a central clipping and examined a correlation between emotional state and fundamental speech frequency. For this purpose, we applied an approach of exploratory data analysis. The ANOVA (Analysis of variance) test confirmed that a modification in the speaker's emotional state changes the fundamental frequency of human vocal tract. The main contribution of the paper lies in investigation, of central clipping method by the ANOVA.


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