A unified framework for sublexical and linguistic modelling supporting flexible vocabulary speech understanding
Raymond Y.K. Lau, Stephanie Seneff · 1998
In [9], we introduced the ANGIE framework for modelling speech where morphological and phonological substructures of words are jointly characterized by a context-free grammar and represented in a multi-layered hierarchical structure. In [6], we demonstrated a competitive word-spotter based on the ANGIE framework and presented several results comparing the performance of various sublexical filler models. In the present work, completed as a part of [5], we extend the ANGIE framework to a competitive full continuous speech recognition system. Furthermore, given that ANGIE is based on a context-free framework, we have decided to combine ANGIE with TINA ([8]), a contextfree based framework for natural language understanding, into an integrated system. The integrated system led to a 21.7% reduction in word error rate compared to a baseline word bigram recognizer on ATIS. Numerous issues relating to the construction of the combined system were explored. We have also examined the addition of n...