Extraction of Excitation Information from Speech and Its Applications for Expressive Speech Processing

Through speech production mechanism, speech with different voice qualities such as phonations, emotions, expressive singing and other paralinguistic sounds are also produced. Most of these sounds demonstrate these features mostly due to the excitation component (vibration of the vocal folds at the glottis) whereas the dynamic vocal tract system primarily conveys the message. Hence, the excitation source processing acquires significance especially for the analysis, detection and representation of expressive voices. Most of the existing excitation source information extraction methods are not reliable especially when applied on expressive voices, mainly due to significant source-system coupling. Hence, there is a need for new signal processing methods that can capture the dynamic variations in excitation source so that different types of sounds can be better analyzed and represented. The objective of this work is to derive new signal processing methods to extract the excitation source information directly from the signal and then investigate the significance of this information for the analysis and detection of various expressive voices. Towards this, some of the excitation source features are extracted using recently proposed signal processing methods and then the significance of these excitation features are studied in emotional speech analysis and recognition. Presently the studies are in progress in representing the excitation source in the form of impulse-like sequence.