A Novel Methodology for Identification of Unclassified Digital Voice
Parthraj Tripathi, N. Satish Kumar · 2013
Voice signals are encoded with various techniques to exploit communication resources such as source, channel, computation and cost of operation. These encoded signals are generally multiplexed with same/different signal type (data, say). At the receiver end, after the data and voice signals are discriminated, the voice bit stream has to be passed through the respective decoder in order to get meaningful audio. Identification of correct decoder requires a digital voice classifier. The importance of such classification before decoding get especially noticed in the cases of design of universal voice decoder where the unknown/unclassified bit stream is expected as of one of the codec out of many types of codec. We call the set of all expected decoders as an ensemble. In this paper, a concept of operation of digital voice classifier before decoder is proposed .This proposed method is superior to method of subjecting a given unclassified bit stream to each of the decoder in a given ensemble. Also, a novel technique called ‘SWOB’ (sliding-window on bit stream) is introduced which gives satisfactory results of classification when used along with methods of auto correlation(AC) and central second order moment(SOM). Another parameter for crisp classification is also introduced which is named as BRO (binary ratio). In all, the (SWOBBRO-SOMAC) algorithm is capable of identifying the digital voice signal classes like of PCM-µ/A law, ADPCM 16-, 24-, 32-, 40 kbps. Using same algorithm, option of coarse classification is open on signals of other type too.