A new method to distinguish non-voice and voice in speech recognition

we addressed the problem of remove the non-voice disturbance in speech recognition. It is always a big problem that the system will wrongly recognize our natural sound, like cough, breath, or sound of lip, nose as speech input and give “recognized ” words output, when we use a speech recognition system. As we know, such non-voice speech is unavoidable for natural speaking, and if we don’t supply effective control, the performance often drops to unacceptable level [1]. This paper puts forward a new method to detect fundamental frequency, and use it to distinguish real speech input and non-voice sound, like breath, lip, or noise by people walking by. Applying this method into our command recognition system, we get good results and make the system very robust and could be used in real life. Key-words Voice distinction Auto-relation Fundamental frequency endpoint detection