Author: Harry Bratt

We describe a method for developing a statistical language model (SLM) with high keyword spotting accuracy for a natural language interface (NLI). The NLI is based on the Adaptive Agent Oriented Software Architecture (AAOSA).

The EduSpeak(TM) system is a software development toolkit that enables developers of interactive language education software to use state-of-the-art speech recognition and pronunciation scoring technology.

We describe SRI’s large vocabulary conversational speech recognition system as used in the March 2000 NIST Hub-5E evaluation.

We describe the methodologies for collecting and annotating a Latin-American Spanish speech database. We use the annotated database to investigate rater reliability, the effect of each phone on overall perceived nonnativeness, and the frequency of specific pronunciation errors.

This paper describes our work in developing multilingual (Swedish and English) speech recognition systems in the ATIS domain. The acoustic component of the multilingual systems is realized through sharing Gaussian codebooks across Swedish and English allophones.

We present a novel approach to hidden Markov model (HMM) state clustering based on the use of broad phone classes and an allophone class entropy measure. Our algorithm allows clustering across allophone class boundaries by defining broad phone groups within which two states from different allophone classes can be clustered together.