Forensic speaker recognition in Chinese: a multivariate likelihood ratio discrimination on /i/ and /y/
نویسندگان
چکیده
A likelihood-ratio-based forensic speaker discrimination was conducted using the mean formant frequencies of Standard Chinese /i/ and /y/ tokens produced by 64 male speakers. The speech data were relatively forensically realistic in that they were relatively extemporaneous, were recorded over the telephone, and were from three non-contemporaneous recording sessions. A multivariate-kernel-density formula was used to calculate cross-validated likelihood ratios comparing all possible same-speaker and different-speaker combinations across sessions. Results were comparable with those previously obtained with laboratory speech in other languages. In general, greater strength of evidence was obtained for recording sessions separated by one week than for recording sessions separated by one month.
منابع مشابه
The effect of correlation on strength of evidence estimates in Forensic Voice Comparison: uni- and multivariate Likelihood Ratio-based discrimination with Australian English vowel acoustics
The consequences of ignoring correlations between features in traditional forensic speaker recognition are investigated. Two likelihood ratio-based discrimination experiments on the same multivariate formant data are described, one taking correlation into account and the other not doing so. The discrimination is performed using Naïve Bayes univariate, and multivariate generative Likelihood Rati...
متن کاملBeyond the long-term mean: exploring the potential of F0 distribution parameters in traditional forensic speaker recognition
Despite its many prima facie attractive properties for Forensic Speaker Recognition, F0 is regarded as having limited forensic value due to its large within-speaker variability. However, its forensic use to date has been limited mostly to its long-term mean and standard deviation. This paper examines the discriminatory potential, within a Likelihood Ratio-based approach, of additional parametri...
متن کاملAutomatic-type calibration of traditionally derived likelihood ratios: forensic analysis of australian English /o/ formant trajectories
A traditional-style phonetic-acoustic forensic-speakerrecognition analysis was conducted on Australian English /o/ recordings. Different parametric curves were fitted to the formant trajectories of the vowel tokens, and cross-validated likelihood ratios were calculated using a single-stage generative multivariate kernel density formula. The outputs of different systems were compared using Cllr,...
متن کاملLinguistic-acoustic Forensic Speaker Identification with Likelihood Ratios from a Multivariate Hierarchical Random Effects Model: a “non-idiot’s Bayes” Approach
The discriminant performance of a likelihood ratio based on a two-level multivariate model is examined on the speech of 60 male Japanese speakers using non-contemporaneous telephone recordings over uncontrolled channels. The performance is determined for both F-pattern centre frequencies and LPC cepstral coefficients, extracted from three very different phonetic segments only: a vowel, a voicel...
متن کاملEstimated Intra-Speaker Variability Boundaries in Forensic Speaker Recognition Casework
Current automatic forensic speaker recognition algorithms are known to be highly dependent on matched reference data for producing statistically reliable outcomes. In day-to-day forensic casework, this data is often not available. This paper addresses this problem by introducing a data-driven modular method which does not require precise reference data. Results are more general and given as p-v...
متن کامل