5th International Conference on Spoken Language Processing
Previously, 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. We also demonstrated a phonetic recognizer and a word-spotter based on ANGIE. In this work, we extend ANGIE to a competitive continuous speech recognition system. Furthermore, given that ANGIE is based on a context-free framework, we have decided to combine ANGIE with TINA, a context-free based framework for natural language understanding, into an integrated system. The integration led to a 21.7% reduction in word error rate compared to a baseline word bigram recognizer on ATIS. We also examined the addition of new words to the vocabulary, an area we believe will benefit from both ANGIE and the ANGIE-plus-TINA integration. The combination reduced error rate by 20.8% over the baseline and outperformed several other configurations tested not involving an integrated ANGIE-plus-TINA.
Bibliographic reference. Lau, Raymond / Seneff, Stephanie (1998): "A unified framework for sublexical and linguistic modelling supporting flexible vocabulary speech understanding", In ICSLP-1998, paper 0053.