Language-model look-ahead for large vocabulary speech recognition

In this paper, we present an efficient look-ahead technique which incorporates the language model knowledge at the earliest possible stage during the search process. This so-called language model look-ahead is built into the time synchronous beam search algorithm using a tree-organized pronunciation lexicon for a bigram language model. The language model look-ahead technique exploits the full knowledge of the bigram language model by distributing the language model probabilities over the nodes of the lexical tree for each predecessor word. We present a method for handling the resulting memory requirements. The recognition experiments performed on the 20000-word North American Business task (Nov.'96) demonstrate that in comparison with the unigram look-ahead a reduction by a factor of 5 in the acoustic search effort can be achieved without loss in recognition accuracy.