Ahots iruzurtiak detektatzenSpoofing Challenge 2015

  1. Jon Sanchez 1
  2. Ibon Saratxaga 1
  3. Inma Hernaez 1
  4. Eva Navas 1
  5. Daniel Erro 2
  1. 1 Aholab, UPV/EHU
  2. 2 Aholab, UPV/EHU, Ikerbasque
Aldizkaria:
Euskalingua

ISSN: 1695-7458

Argitalpen urtea: 2016

Zenbakia: 28

Orrialdeak: 33-38

Mota: Artikulua

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Beste argitalpen batzuk: Euskalingua

Laburpena

This 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.

Datuen iturria: Dialnet