In this paper, we explore statistical language modelling for a speech-enabled MP3 player application by generating a corpus from the interpretation grammar written for the application with the Grammatical Framework (GF) (Ranta, 2004). We create a statistical language model (SLM) directly from our interpretation grammar and compare recognition performance of this model against a speech recognition grammar compiled from the same GF interpretation grammar. The results show a relative Word Error Rate (WER) reduction of 37% for the SLM derived from the interpretation grammar while maintaining a low in-grammar WER comparable to that associated with the speech recognition grammar
