VowelRegionbasedSpeechAnalysis andApplications

Abstract

Speech signal can be considered as a sequence of acoustic events, where each acoustic event can be distinctly characterized by its production mechanism. Acoustic event-based signal processing techniques have gained vital importance in speech feature representation which is robust to noise. The detection of specific acoustic events that correspond to the unique phonetic features of the speech is important in speech assessment systems and clinical speech analysis. In landmark or acoustic event based speech analysis, the speech signal is processed around specific locations known as events instead of the entire speech signal. Most of the Indian languages are vowel-centric, and hence consonants must be grouped with a vowel following it or preceding it. This process of clustering consonant or consonant cluster with either preceding vowel or next vowel is known as syllabification. The significance of accurate vowel region detection from a continuous speech has many applications that include robust speaker recognition, smart audio filtering, consonant-vowel unit recognition in Indian languages, speech rate manipulation and multimedia synchronization. With this motivation, the thesis explores the use of speech production knowledge in the detection of vowel regions. Further, the vowel region detection techniques are used to detect retroflex approximants and palatalized consonants in the Indian context newline