Efficient approximated i-vector extraction

I-vectors are currently widely used by state-of-the-art speech processing systems for tasks such as speaker verification and language identification. A shortcoming of i-vector-based systems is that the i-vector extraction process is computationally expensive. In this paper we propose an efficient me...

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Bibliographic Details
Published in2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 4789 - 4792
Main Authors Aronowitz, H., Barkan, O.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2012
Subjects
Accuracy
approximated i-vectors extraction
Approximation methods
Degradation
efficient speaker recognition
i-vectors
Speaker recognition
Speech processing
Vectors
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Summary:I-vectors are currently widely used by state-of-the-art speech processing systems for tasks such as speaker verification and language identification. A shortcoming of i-vector-based systems is that the i-vector extraction process is computationally expensive. In this paper we propose an efficient method to extract i-vectors approximately. The method normalizes the GMM counts to be similar across sessions. We validate our method empirically for the speaker verification task on five different datasets, both text independent and text dependent. A significant speedup was obtained with a very small degradation in accuracy compared to the standard exact method.
ISBN:1467300454
9781467300452
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2012.6288990