COST278 and ISCA Tutorial and Research Workshop (ITRW) on Robustness Issues in Conversational Interaction University of East Anglia, Norwich, UK August 30-31, 2004

Adding Robustness to Language Models for Spontaneous Speech Recognition

Jacques Duchateau, Tom Laureys, Patrick Wambacq

Katholieke Universiteit Leuven - ESAT, Leuven, Belgium

Compared to dictation systems, recognition systems for spontaneous speech still perform rather poorly. An important weakness in these systems is the statistical language model, mainly due to the lack of large amounts of stylistically matching training data and to the occurrence of disfluencies in the recognition input. In this paper we investigate a method for improving the robustness of a spontaneous language model by flexible manipulation of the prediction context when disfluencies occur. In the case of repetitions, we obtained significantly better recognition results on a benchmark Switchboard test set.

Full Paper

Bibliographic reference.  Duchateau, Jacques / Laureys, Tom / Wambacq, Patrick (2004): "Adding robustness to language models for spontaneous speech recognition", In Robust2004, paper 11.