Ahots iruzurtiak detektatzen : Spoofing Challenge 2015

EuskaraArtikulu honetan Aholabek garatutako Ahots Sintetikoaren Detektorea (Synthetic Speech Detector, SSD) deskribatzen da, eta bere erabilera Automatic Speaker Verification Spoofing and Countermeasures Challenge (ASVspoof 2015) nazioarteko norgehiagokan. GMMtan oinarritutako detektorea da, non ereduak Relative Phase Shift (RPS) fasearen informaziorako transformazioa erabiliz osatzen diren. Estrategia desberdinak ebaluatzen dira: eraso espezifikoen ereduak sortu norgehiagokaren antolatzaileek emandako informazioaren bidez, edo mehatxu-seinaleak sortzeko erabili omen den bokoderraren ereduak sortu, aurreko lanetan garatutako informazioa erabiliz. Ebaluazioaren emaitzetan ikusten denez, eraso espezifikoen ereduak ondo aritzen dira eraso ezagunekin, baina ez ezezagunekin. Bokoderren ereduak erabiltzen direnean, informazioa ez da guztiz erabiltzen eta ereduen moldaketa landu behar da. EnglishThis paper introduces the Synthetic Speech Detection system developed by Aholab for the Automatic Speaker Verification Spoofing and Countermeasures Challenge (ASVspoof 2015). The detector is a classifier based on Gaussian Mixture Models that are created using the Relative Phase Shift (RPS) transformation for the phase information. Different strategies have been evaluated: modeling the specific attacks using the information provided by the ASVspoof 2015 organizers, and modeling the vocoders possibly used in the spoofing signals, using data from previous works. The evaluation results show that attack specific models work for known attacks but they do not cope with the unknown attacks correctly. When using vocoder models build with other databases, the results suggest that the followed strategy do not take advantage of the available data and thus model adaptation should be explored.