Nikiforov
Vladimir O.
D.Sc., Prof.
doi: 10.17586/2226-1494-2015-15-1-70-77
SPEAKERS' IDENTIFICATION METHOD BASED ON COMPARISON OF PHONEME LENGTHS STATISTICS
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For citation: Bulgakova E.V., Sholokhov A.V., Tomashenko N.A. Speakers' identification method based on comparison of phoneme lengths statistics. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2015, vol. 15, no. 1, pp. 70–77 (in Russian)
Abstract
Subject of research. The paper presents a semi-automatic method of speaker identification based on prosodic features comparison - statistics of phone lengths. Due to the development of speech technologies in recent times, there is an increased interest in searching of expert methods for speaker's voice identification, which supplement existing methods to increase identification reliability and also have low labour intensity. An efficient solution for this problem is necessary for making the reliable decision whether the voices of the speakers in the audio recordings are identical or different.
Method description. We present a novel algorithm for calculating the difference of speakers’ voices based on comparing of statistics for phone and allophone lengths. Characteristic feature of the proposed method is the possibility of its application along with the other semi-automatic methods (acoustic, auditive and linguistic) due to the lack of a strong correlation between analyzed features. The advantage of the method is the possibility to carry out rapid analysis of long-duration recordings because of preprocessing automation for data being analyzed. We describe the operation principles of an automatic speech segmentation module used for statistics calculation of sound lengths by acoustic-phonetic labeling. The software has been developed as an instrument of speech data preprocessing for expert analysis.
Method approbation. This method was approved on the speech database of 130 speech records, including the Russian speech of the male speakers and female speakers, and showed reliability equal to 71.7% on the database containing female speech records, and 78.4% on the database containing male speech records. Also it was experimentally established that the most informative of all used features are statistics of phone lengths of vowels and sonorant sounds.
Practical relevance. Experimental results have shown applicability of the proposed method for the speaker recognition task in the course of phonoscopic examination.
Acknowledgements. Работа выполнена при государственной финансовой поддержке ведущих университетов Российской Федерации (субсидия 074-U01).
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