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.