Internet Documents: A Rich Source for Spoken Language Modeling

Spoken language speech recognition systems need better understanding of natural spoken language phenomenon than their dictation counterparts. Current language models are mostly based on written text and/or very tedious Wizard of Oz or real dialog experiments. In this paper we propose to use Internet documents as a very rich source of information for spoken language modeling. Through detailed experiments we show how using Internet we could automatically prepare language models adapted to a given task. For a given recognition system using this approach the word accuracy is up to 15% better than a system using language models trained on written text.