Robust Speech Recognition Technology Program Summary

The major objective of this program is to develop and demonstrate robust, high-performance continuous speech recognizer (CSR) techniques and systems focused on application in spoken language systems (SLS). A key supporting objective is to develop techniques for integration of CSR and natural language processing (NLP) systems in SLS applications. The CSR techniques are based on a continuous-observation Hidden Markov Model (HMM) approach, which has previously demonstrated high performance for normal speech and robustness for stressed speech. The motivation is that current state-of-the-art CSR systems must be improved in performance and robustness for advanced SLS environments, with variabilities including those due to spontaneous speech, noise, and task-induced stress. The effort in CSR/NLP integration is focused on development of a structured CSR/NLP interface, which will allow effective collaboration with and between other groups developing NLP and/or CSR systems.