Painless WFST cascade construction for LVCSR - transducersaurus
Josef R. Novak, Nobuaki Minematsu, Keikichi Hirose · 2011
This paper introduces the Transducersaurus toolkit which provides a set of classes for generating each of the fundamental components of a typical WFST ASR cascade, including a Context-dependency transducer, a Lexicon, a stochastic language model and an optional silence class model. The toolkit further implements a simple scripting language in order to facilitate the construction of cascades with a variety of popular combination and optimization methods and provides integrated support for the T 3 and Juicer WFST decoders, and both Sphinx and HTK format acoustic models. New results for two standard WSJ tasks are also provided, comparing a variety of cascade construction and optimization algorithms. These results illustrate the flexibility of the toolkit as well as the tradeoffs inherent in various build algorithms. Index Terms: Speech Recognition, WFST, LVCSR