Universal semi-word model for vocabulary contraction in automatic speech recognition

A speech recognition system includes, or has access to, conventional speech recognizer data, including a conventional acoustic model and pronunciation dictionary. The speech recognition system generates restructured speech recognizer data from the conventional speech recognizer data. When used at runtime by a speech recognizer module, the restructured speech recognizer data produces more accurate and efficient results than those produced using the conventional speech recognizer data. The restructuring involves segmenting entries of the conventional pronunciation dictionary and acoustic model according to their constituent phonemes and grouping those entries with the same initial N phonemes, for some integer N (e.g., N=3), and deriving a restructured dictionary with a corresponding semi-word acoustic model for the various grouped entries. The decomposition of the conventional pronunciation dictionary into the restructured dictionary with semi-word acoustic model greatly reduces the number of possibilities in the dictionaries (e.g., from potentially unlimited to finite and relatively small), and also improves the accuracy of speech recognition.