Open-set speaker identification with diverse-duration speech data

Rawande Karadaghi; Heinz Hertlein; Aladdin Ariyaeeinia

doi:10.1117/12.2176335

15 May 2015 Open-set speaker identification with diverse-duration speech data

Rawande Karadaghi, Heinz Hertlein, Aladdin Ariyaeeinia

Proceedings Volume 9457, Biometric and Surveillance Technology for Human and Activity Identification XII; 94570G (2015) https://doi.org/10.1117/12.2176335
Event: SPIE Defense + Security, 2015, Baltimore, MD, United States

Abstract

The concern in this paper is an important category of applications of open-set speaker identification in criminal investigation, which involves operating with short and varied duration speech. The study presents investigations into the adverse effects of such an operating condition on the accuracy of open-set speaker identification, based on both GMMUBM and i-vector approaches. The experiments are conducted using a protocol developed for the identification task, based on the NIST speaker recognition evaluation corpus of 2008. In order to closely cover the real-world operating conditions in the considered application area, the study includes experiments with various combinations of training and testing data duration. The paper details the characteristics of the experimental investigations conducted and provides a thorough analysis of the results obtained.

Citation Download Citation

Rawande Karadaghi, Heinz Hertlein, and Aladdin Ariyaeeinia "Open-set speaker identification with diverse-duration speech data", Proc. SPIE 9457, Biometric and Surveillance Technology for Human and Activity Identification XII, 94570G (15 May 2015); https://doi.org/10.1117/12.2176335

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