Abstract
An experiment carried out on speaker identification by semi-automatic measurement of parameters with the goal of collaborating numerical data as well as descriptive data with that of probability scales. The 15 sets of speech samples of 15 speakers selected randomly from 100 actual crime cases, in Hindi utterances for purpose of speaker identification test subjected to spectrographic analysis. Speaker specific acoustic parameters, namely 1st formant frequency at a particular location (F1); 2nd formant frequency at a particular location (F2); and 3rd formant frequency at a particular location (F3) measured for the set of speech samples for all the 15 speakers. Also, the auditory analysis based on the linguistic features and phonetic features noted of each of the 15 sets of speech samples. We developed software to calculate the similarity percentage for the numerical data measured on the basis of acoustic analysis and numerical values assigned to auditory parameters on the basis of auditory analysis computed according to one of the nine probability scales. Most of the existing methods take only acoustic features to obtain numerical results for the purposes of speaker identification.
Highlights
The fast increasing development and penetration of communication technology surely helped humankind in better, accessible and efficient communication but it is not without its ill consequences
Information and Communication technology (ICT) has helped anti-social elements in committing more organized and white collar crimes, and in turn, law enforcement agencies should be better equipped with advanced technology to counter or deal with such crimes
Et al [5] in one of their experiment professed that the differences between inter-speaker and intra-speaker variability, which according to them, stems mainly from the anatomical differences in vocal tract but these did not correlate or quantified with specific acoustic parameters
Summary
The fast increasing development and penetration of communication technology surely helped humankind in better, accessible and efficient communication but it is not without its ill consequences. Information and Communication technology (ICT) has helped anti-social elements in committing more organized and white collar crimes, and in turn, law enforcement agencies should be better equipped with advanced technology to counter or deal with such crimes. Identification technology is one of the many tools which our law enforcement agencies could rely upon and it is a popular identification technique used for monitoring and authenticating human subjects using their speech signal. The question often arises about how to involve auditory parameters in numerical terms in the results of speaker identification [1,2]. Et al [5] in one of their experiment professed that the differences between inter-speaker and intra-speaker variability, which according to them, stems mainly from the anatomical differences in vocal tract but these did not correlate or quantified with specific acoustic parameters
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