Determining the Likelihood Ratio From Perceptual Attributes of Voice.

To provide voice experts with a method for determining the likelihood ratio (LR) from the perceptual evaluation of distinctive voice attribute scores. The proposed method aims to obtain the similarity and typicality judgments made by forensic voice experts (FVEs) during the comparison of attributes...

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Published in:Journal of Voice Vol. 38; no. 4; pp. 816 - 817
Main Authors: Gurlekian, Jorge A., Suligoy, Stefania, Univaso, Pedro, Torres, Humberto, Masessa, Evangelina, Molina, Nancy
Format: research Journal Article
Published: Elsevier B.V. Jul2024
Online Access:View this record in EBSCOhost
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      dt: Jul2024
      vid: 38
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      pub: Elsevier B.V.
      place: New York, New York
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        178423532
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        10.1016/j.jvoice.2022.01.022
        178423532
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        atl: Determining the Likelihood Ratio From Perceptual Attributes of Voice.
      aug:
        au:
          Gurlekian, Jorge A.
          Suligoy, Stefania
          Univaso, Pedro
          Torres, Humberto
          Masessa, Evangelina
          Molina, Nancy
        affil: Laboratorio de Investigaciones Sensoriales (LIS) INIGEM, Science and Justice Program, National Council of Scientific and Technological Research, Hospital de Clinicas, Ciudad de Buenos Aires, Argentina
      sug:
        subj:
          Voice Perception
          Forensic Sciences
          Probability
          Human
          Comparative Studies
          Descriptive Statistics
          Listening
          Male
          Female
          Male
          Female
      ab: To provide voice experts with a method for determining the likelihood ratio (LR) from the perceptual evaluation of distinctive voice attribute scores. The proposed method aims to obtain the similarity and typicality judgments made by forensic voice experts (FVEs) during the comparison of attributes in voice pairs. It is based on the scoring method for LR calculation. In the first stage, 17 perceptual attributes grouped into six vocalic categories are specified. A novel graphical interface is used to obtain discriminative responses both globally and for each attribute from ten pairs of test sentences produced by the same and different speakers. The FVEs should discriminate whether the attributes are similar or different in each pair and should indicate the degree to which the attributes are present. In addition, for six specific attributes, the FVEs must decide whether the attribute is typical or atypical in the reference population. In the second stage, the mean score obtained in the first stage is converted to LR using probability density functions of listeners' responses to 1680 same/different speaker pairs discriminated for female and male speakers. The responses of the FVEs to the test pairs show the discriminatory power of the attributes, the incidence of the typicality factor on the final score and the performance of each FVE. With the application of the probability density functions obtained for the responses to pairs of the same or different origin taken from the reference population, the final scores are converted into LRs that are compared with the true conditions of each pair. The application of the developed system allows the global and discriminated evaluation of the perceptual attributes with high agreement in the comparison of pairs of voices. Obtaining the LRs allows associating the perceptual evaluation method with the automatic methods that are used nowadays. The responses of the FVEs taken as a reference, will allow training and evaluating the performance of young FVEs.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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