Development of Kannada speech corpus for prosodically guided phonetic search engine

Development and availability of spoken language corpora in regional languages is of utmost importance for a multicultural and multilingual country like India. The issues of regional bias, accent, unique style and diversity associated with each geographical region and language will have a significant effect on the performance of speech recognition/synthesis systems. In this paper, collection of speech data in Kannada language for prosodically guided phonetic search engine and the issues involved in transcription are explained. The speech corpus consists of data in three different contexts namely, read mode, conversation mode and extempore mode. A four layered transcription namely, phonetic transcription using IPA symbols, syllabification, pitch marking and break marking is done for the entire data. A baseline recognition system for Kannada language is built using HTK for the data collected in different modes and the results are presented.