Patent Document ID: 8532991
Application ID: 12720968

Base Claim:
1. A method of training a speech model, comprising: obtaining model parameters for the speech model; processing a known speech input using the speech model with the model parameters to generate a process result; calculating a distance between a true result and the process result, given the model parameters and the known speech input, the true result comprising a true transcription, the true transcription corresponding to only the following waveform states: silence, noise, onset and speech, instead of a phonetic transcription; and modifying the model parameters to reduce the distance between the true result and the process result, to obtain a modified model, wherein reducing the distance between the true result and the process result comprises maximizing a function comprising a parameter set for an acoustic model and a super utterance, the super utterance comprising a feature vector sequence, the true result and the process result.

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Claim 5:
5. The method of claim 1 wherein the speech model comprises a speech detection model, and wherein processing a known speech input to generate a process result comprises: performing speech detection on acoustic data indicative of an input signal to generate a detection state output indicative of a decision made by the speech detection model as to whether the input signal represents speech or non-speech.