Author: Kristin Precoda

This paper describes the development of a concept annotation method for evaluating a narrow domain speech-to-speech translation system and discusses how the scores produced by that method relate to naïve human judgements about the quality of translations.

We describe the development and conceptual evolution of handheld spoken phrase translation systems, beginning with an initial undirectional system for translation of English phrases, and later extending to a limited bidirectional phrase translation system.

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).

Predicting the degree of nativeness of a student’s utterance is an important issue in computer-aided language learning.

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.

This study’s goal was to determine whether receiving a particular type of feedback on nativeness of second-language accent positively influenced pronunciation over time.