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Title: Comparison of speaker verification performance for adult and child speech
Authors: Safavi, Saeid 
Najafian, Maryam 
Hanani, Abualsoud 
Russell, Martin 
Jančovič, Peter 
Keywords: Automatic speech recognition;Biometric identification;Machine learning;Child speech recognition;Gaussian mixture model;Bandwidth;PF-STAR;ABI-1;ABI-2
Issue Date: 2014
Abstract: Although speaker verification is an established area of speech technology, previous studies have been restricted to adult speech. This paper investigates speaker verification for children’s speech, using the PF-STAR children’s speech corpus. A contemporary GMM-based speaker verification system, using MFCC features and maximum score normalization, is applied to adult and child speech at various bandwidths using comparable test and training material. The results show that the Equal Error Rate (EER) for child speech is almost four times greater than that for adults. A study of the effect of bandwidth on EER shows that for adult speaker verification, the spectrum can be conveniently partitioned into three frequency bands: up to 3.5-4kHz, which contains individual differences in the part of the spectrum due to primary vocal tract resonances, the region between 4kHz and 6kHz, which contains further speaker-specific information and gives a significant reduction in EER, and the region above 6kHz. These finding are consistent with previous research. For young children’s speech a similar pattern emerges, but with each region shifted to higher frequency values.
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