Classification of speech is one of the most vital problems in speech processing.
Although there have been many studies on the classification of speech, the results are still limited.
The average performance in the classification of speech under stress was improved by 10%to15%5% using the proposed features, compared to traditional methods of stressed speech classification.
The classification of speech can be done into five categories depending upon the modes of speech production i.e. difference in vocal efforts[3].
At this point (for ), the correct classification of speech was about 78% and the correct classification of noise was about 50% (see Figure 3).
Although the pauses in each type of speech were characterized in numerous analyses (e.g., [33 35]), there has been a lack of automatic classification of speech type based on silent pause-related cues only.
However, the features examined in these previous studies lack a physical basis, and the methods do not consider the whole process of speech production, which is believed to be essential for effective classification of speech under stress.
Because we would like to recognize four emotional speech styles and two basic types of gender, we need to obtain four trained emotion models for classification of speech pronounced by male speakers and four models for classification of sentences spoken by female speakers, and two summary models for gender recognition (trained on the data of sentences pronounced in all classified emotional styles).
Since the Fujisaki model commands are anchored to the syllabic layer (see Section 2) and we did not require an exact local estimate of speech rate, but a broad classification of speech rate on the utterance level, the following investigation is performed with respect to the syllabic rate.
This neuropsychological research strategy has been applied using tasks requiring explicit classification of speech sounds embedded in meaningless syllables (Meister et al. 2007; D'Ausilio et al. 2009; Möttönen and Watkins 2009; for reviews, see Möttönen and Watkins 2012; Murakami et al. 2013).
