Linear Prediction of Speech
Analysis and compensation of stressed and noisy speech with application to robust automatic recognition
Analysis, synthesis, and recognition of stressed speech
Analysis, synthesis, and recognition of stressed speech
Spoken emotion recognition using glottal symmetry
EURASIP Journal on Advances in Signal Processing - Special issue on emotion and mental state recognition from speech
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Two areas of speech processing that continue to be important are analysis of stressed speech and glottal modelling. This paper reports two new developments in the combination of these two areas, that is, analysis of the glottal excitation of stressed speech. First, a simple pattern recognition principle is used to show that, gven an unknown glottal waveform, the style can be correctly identified with roughly 90% accuracy. Deviant styles such as angry, loud, and soft can be correctly identified with accuracy approaching 100%. These results confirm the importance of the glottal excitation in conveying stress and in contributing to the variability of speech waveforms. Second, several speaking style modification algorithms have been developed and are reported here. These algorithms are able to modify styled speech to sound more normal and normal speech to sound styled. In one example, subjective listening tests demonstrate that styled speech can be modified to sound significantly more normal with these algorithms.