New Developments in Lattice-Based Search Strategies in SRI’s Hub4 System

Abstract

We describe new developments in SRI’s lattice-based progressive search strategy. These developments include the implementation of a new bigram lattice algorithm, lattice optimization techniques, and expansion of bigram lattices to trigram lattices. The new bigram lattice generation algorithm is based on generation of backtrace entries using a word-dependent N-best list decoding pass, followed by lattice generation from the backtrace entries. We present an algorithm to reduce the size of the bigram lattices while maintaining all valid paths. This algorithm is shown to reduce the size of the lattice by about 5065533; allowing easier processing in later stages such as expansion to trigram lattices. We describe two algorithms to expand bigram lattices to trigram lattices. The first is a conventional method, while the second is a novel approach that results in compact trigram lattices that were found to be a factor of six smaller than lattices created with the conventional approach. Decoding with the new trigram lattices gave a 5% improvement in word error rate as compared to our previous search strategy which used trigram LMs to rescore N-best lists.