DETECTION OF ETHNO-LINGUAL IDENTITY USING ARTIFICIAL INTELLIGENCE, MACHINE LEARNING AND VOICE ANALYSIS TOOLS: INTRODUCING “AUTOMATED CRIMINAL ETHNICITY IDENTIFICATION SYSTEM” (ACEIS)

Abstract

Voice evidence is also known as voiceprint like fingerprint, it has been proven to substantiate the findings. Voiceprint is a dissimilar character for different people. In forensic science sometimes, we come across cases where the suspect’s or victim’s ethnicity has to be identified using various number of identification factors like voice, physical and anthropological features etc. In such cases the examination of an individual’s ethnicity may be identified using the other available identification factors but when it comes to the Ethno-Lingual identification then examining the individual’s language for the same and that too without any digital tool, i.e., doing it manually, becomes a sturdy task for the examiner. The database of the voice samples of Hindi, English and Mother language has been successfully created by the authors which is named as the “Automated Criminal Ethnicity Identification System” (ACEIS). In this paper, the author has summarised the various studies conducted on the ethno-lingual identification and their acquisition. Based on the studies, it was concluded in the review that the use of Artificial Intelligence and Machine Learning was used in prior studied but in India it hasn’t been done yet. When known samples were analysed for their ethnicity, we noticed that an 80% matching was there among the samples belonging from same ethnicity. This matching-percentage was calculated on the basis of Pitch, Amplitude, Formant Frequencies, Frequencies and the average time taken to speak a word/letter etc.