Abstract
The main purpose of this paper is Conversion of non- audible murmured voice into the normal speech using Hidden Markov Model(HMM).This non audible murmur voice NAM is a one type of murmured voice which can be delivered by a NAM microphone which is attached behind the speaker’s ear. The Hidden Markov Models(HMMs) are stochastic models of statistical learning .These are very useful in speech recognition .The point of the paper is to collect as much as data from the device and convert it into audible and clear data signal that can be used for further sensory based applications. Hence, having an insight of how to convert the NAM to speech and then to whisper has a lot of benefits while keeping in mind the disadvantages of such conversion. Since, NAM is minute details of a communication between one’s own self it is highly recommended to the data in as much as discrete format as necessary since a speech signal can have various frequencies over a portion of the signal, big data approach is recommended.
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