Hmm decoding with acoustic model compensation for phoneme modeling and pronunciation modelings

Abstract

Described are techniques to recognize spoken wake word (WW) or command for human-machine interface using a speech recognition system that does not require any WW or command-matching speech data for training. The system uses the text or grapheme representation of the WW or commands for training before deployment. The technique includes generating a matrix of statistics characterizing phonetic modeling of an acoustic model that distinguishes speech signals according to a plurality of acoustic units of a language. It further includes constructing a speech recognition model based on the matrix of statistics to recognize a target phrase in speech. It further includes processing an audio signal based on the acoustic model and the speech recognition model to detect a presence of the target phrase.

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