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Prosodic Analysis of a German Read Corpus for a CAL L System for Rehabilitation Purposes

Now-a-days Computer Assisted Language Learning (CALL) systems for rehabilitation purposes involving rhythmic analysis and prosodic analysis which are inter-related have gained much importance in speech synthesis and recognition systems. The main objective is to develop a language learning system and content data corresponding to the pronunciation training of German and Slavic languages. The call system AzAR (German acronym for ‘automat for accent reduction’) which was developed at our IAS laboratory provides adequate feedback regarding the pronunciation of the learner as well as the prosodic quality. With regard to learners and teachers, the new feature is the integration of large corpus and multilingual data bases. The motivation for this kind of analysis is that prosodic features carry a substantial part of the language identity that may be sufficient for humans to perceptually identify some languages. The main objective of the present work is to demonstrate the significance of limited German phoneme rhythmic based prosodic variations in frequency f0, duration and intensity and to develop rhythmic unit extraction model for speech synthesis and recognition. This work starts with rhythmic based prosodic analysis, an accent and de-accent experiment using resynthesis and a perceptual test. The improved perceptual quality of the duration and mean frequency modified phonemes proved to be a promising result for perception as demonstrated in the subjective evaluation test with resynthesis stimuli. The main application leads to develop a multimodel data-based assistance system for self learning activities for old aged people affected with brain related diseases e.g., Parkinson's disease.