Heterogeneous lexical units for automatic speech recognition: preliminary investigations

This paper explores the use of the phone and syllable as primary units of representation in the first stage of a two-stage recognizer. A finite-state transducer speech recognizer is utilized to configure the recognition as a two-stage process, where either phone or syllable graphs are computed in the first stage, and passed to the second stage to determine the most likely word hypotheses. Preliminary experiments in a weather information speech understanding domain show that a syllable representation with either bigram or trigram language models provides more constraint than a phonetic representation with a higher-order n-gram language model (up to a 6-gram), and approaches the performance of a more conventional single-stage word-based configuration