A hybrid method of person verification with use independent speech and facial asymmetry

In a person identification or verification, the prime interest is not in recognizing the words but determining who is speaking the words. In systems of person identification, a test of signal from an unknown speaker is compared to all known speaker signals in the set. The signal that has the maximum probability is identified as the unknown speaker. In security systems based on person identification and verification, faultless identification has huge meaning for safety. In systems of person verification, a test of signal from a known speaker is compared to recorded signals in the set, connected with a known tested persons label. There are more than one recorded signals for every user in the set. In aim of increasing safety, in this work it was proposed own approach to person verification, based on independent speech and facial asymmetry. Extraction of the audio features of person's speech is done using mechanism of cepstral speech analysis. The idea of improvement of effectiveness of face recognition technique was based on processing information regarding face asymmetry in the most informative parts of the face the eyes region.