Integrating statistical and rule-based knowledge for continuous German speech recognition

A new approach to continuous speech recognition (CSR) for German is presented, which integrates both statistical knowledge (at the acoustic-phonetic level) and rule-based knowledge (at the word and sentence levels). We introduce a flexible framework allowing bidirectional processing and virtually any search strategy given an acoustic model and a context-free grammar. An implementation of this class of recognizers by means of a word spotter and an island chart parser is presented. A word recognition accuracy of 93.5% is reported on a speaker dependent recognition task with a 4k words dictionary.