Abstract: This thesis deals with the research and development of speech technology-based systems for the requirements of users with different impairments and disabilities, with the final aim of improving their quality of life. Speech disorders are shown to be a major challenge in the work with these users. This work performs all the steps in the research in speech technologies: starting with the acquisition of an oral corpus from young impaired speakers, the analysis of the acoustic and lexical variations in the disordered speech and the characterization of speaker dependent Automatic Speech Recognition (ASR) systems adapted to the acoustic and lexical variants introduced by these speakers. Furthermore, automated methods for detection and correction of lexical mispronunciations are also evaluated. The results of the experiments show the on-going possibility for developing a fully personalized ASR system for handicapped users that learns the speaker's speech characteristics on-line: while the user interacts with the recognition system. The development of speech therapy tools based on the knowledge gained is another outcome of the present thesis, where the development of "Comunica" aims to improve the possibilities for semi-automated speech therapy in Spanish.
Index Terms: speech disorders, speaker personalization, language learning.