1. A multi-state barge-in acoustic model, the model comprising: a non-speech component comprising two one-state Hidden Markov Models (HMMs) and two three-state left-to-right HMMs; and a speech component comprising five three-state HMMs wherein each of the five three-state HMMs initially represents a different phonetic category.
1. A multi-state barge-in acoustic model, the model comprising: a non-speech component comprising two one-state Hidden Markov Models (HMMs) and two three-state left-to-right HMMs; and a speech component comprising five three-state HMMs wherein each of the five three-state HMMs initially represents a different phonetic category. 3. The model of claim 1 , wherein the model is trained using a maximum likelihood training on data partitioned into speech and non-speech segments.