Integrating a context-dependent phrase grammar in the variable n-gram framework

Focuses on the learning of multi-word lexical units, or phrases, and how to model them within the variable n-gram framework. We introduce the notion of context-dependent phrases and suggest an algorithm for the unsupervised learning of phrases. Also, we propose an approach to integrate a phrase grammar and a variable n-gram without the need to explicitly handle multi-word lexical items. The combined variable n-gram phrase grammar improves recognition accuracy on the Switchboard corpus over both the baseline trigram and using a variable n-gram alone