Annotation and Use of Speech Production Corpus for Building Language-Universal Speech Recognizers

A corpus linguistic study is reported in this paper, guided by articulatory phonology and by general phonetic principles of speech production. A direct application of this study is the construction of Hidden Markov Model topologies for automatic speech recognition, taking into account integrated multilingualism with the consideration of the common physiological organs and processes involved in the production of speech sounds from the world’s languages. We demonstrate in this study that incorporation of speech production principles can provide effective constraints on pronunciation modeling for the purpose of building language-universal speech recognizers.