Item Details

Tuning the performance of automatic speaker recognition in different conditions: effects of language and simulated voice disguise

Issue: Vol 26 No. 2 (2019)

Journal: International Journal of Speech Language and the Law

Subject Areas: Linguistics

DOI: 10.1558/ijsll.39778

Abstract:

Automatic speaker recognition applications have often been described as a ‘black
box’. This study explores the benefit of tuning procedures (condition adaptation and
reference normalisation) implemented in an i-vector PLDA framework ASR system,
VOCALISE. These procedures enable users to open the black box to a certain degree.
Subsets of two 100-speaker databases, one of Czech and the other of Persian
male speakers, are used for the baseline condition and for the tuning procedures.
The effect of tuning with cross-language material, as well as the effect of simulated
voice disguise, achieved by raising the fundamental frequency by four semitones
and resonance characteristics by 8%, are also examined. The results show superior
recognition performance (EER) for Persian than Czech in the baseline condition,
but an opposite result in the simulated disguise condition; possible reasons for this
are discussed. Overall, the study suggests that both condition adaptation and reference
normalisation are beneficial to recognition performance.

Author: Radek Skarnitzl, Maral Asiaee, Mandana Nourbakhsh

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