Dynamic Lexicon for a Very Large Vocabulary Vocal Dictation

Abstract : For very large vocabulary vocal dictation systems, we present a decoding strategy useful to reduce the lexical decoding cost. For each test-utterance, a sub-lexicon is selected from a very large recognition vocabulary. Such a recognition sub-lexicon is called Dynamic Lexicon (DL). Various algorithms of DL selection are developed and tested in terms of coverage rate of textual corpus. From these experiments, we describe a DL constitution we choose to use in D-DAL, our HMM-based recognizer competing for the first campaign of french vocal dictation supported by AUPELF. The contribution made by this original DL is a posteriori confirmed through the AUPELF-B1 test-dictation.