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Effect of combining auditory features with acoustic parameters on the probability scales in forensic speech recognition

Author Affiliations

  • 1Physics Division, Forensic Science Laboratory, Madhuban, Karnal, Haryana, India
  • 2Physics Division, State Forensic Science Laboratory, Delhi, India
  • 3Dept. of Applied Physics, Guru Jambeshwar University of Science and Technology, Hisar, India

Res. J. Forensic Sci., Volume 6, Issue (3), Pages 1-6, April,29 (2018)


Attempts to understand the phenomenon and mechanism of speech sounds led humans to discover visual representation of them in terms of frequency-time graphs which helps them to understand acoustic parameters, which give the voice of humans ‘uniqueness’. One of the emerging field of forensic science is using acoustic parameters and auditory features to perform speaker identification test by comparing known to unknown samples. In this paper, we consider two sets of speech samples, questioned and known specimen speech sample data base obtained from the actual crime cases. The two speech samples underwent to the method of auditory analysis and spectrographic analysis. The percentage of similarities between the unknown sample (Questioned) and the known sample were ascertained by formant frequencies, and for numerical values assigned to the auditory features. Bayes’ Theorem was used to combine objective probability obtained from the acoustic parameters and subjective probability obtained from the auditory features. These values computed to correlate with one of the nine probability scales with the help of the software programs developed by the authors. This study reveals how the resultant probability changes, if auditory features were also taken into account along with that of the acoustic parameters while calculating the final similarity percentage.


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