DOI: 10.17586/2226-1494-2016-16-2-284-289


E. V. Bulgakova, A. V. Sholokhov

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For citation: Bulgakova E.V., Sholokhov A.V. Semi-automatic speaker verification system. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2016, vol. 16, no. 2, pp. 284–289. doi:10.17586/2226-1494-2016-16-2-284-289


Subject of Research. The paper presents a semi-automatic speaker verification system based on comparing of formant values, statistics of phone lengths and melodic characteristics as well. Due to the development of speech technology, there is an increased interest now in searching for expert speaker verification systems, which have high reliability and low labour intensiveness because of the automation of data processing for the expert analysis. System Description. We present a description of a novel system analyzing  similarity or distinction of speaker voices based on comparing statistics of phone lengths, formant features and melodic characteristics. The characteristic feature of the proposed system based on fusion of methods is a weak correlation between the analyzed features that leads to a decrease in the error rate of speaker recognition. The system advantage is the possibility to carry out rapid analysis of recordings since the processes of data preprocessing and making decision are automated. We describe the functioning methods as well as fusion of  methods to combine their decisions.  Main Results. We have tested the system on the speech database of 1190 target trials and 10450 non-target trials, including the Russian speech of the male and female speakers. The recognition accuracy of the system is 98.59% on the database containing records of the male speech, and 96.17% on the database containing records of the female speech. It was also experimentally established that the formant method is the most reliable of all used methods.  Practical Significance. Experimental results have shown that proposed system is applicable for the speaker recognition task in the course of phonoscopic examination.

Keywords: phonoscopic examination, speaker recognition, semi-automatic speaker verification methods, statistics of phone lengths, formant features, melodic characteristics


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