ASASVIcomtech: the Vicomtech-UGR speech deepfake detection and SASV systems for the ASVspoof5 Challenge

  1. Martín-Doñas, Juan M. 1
  2. Rosello, Eros
  3. Gomez, Angel M.
  4. Álvarez, Aitor
  5. López-Espejo, Iván
  6. Peinado, Antonio M.
  1. 1 Universidad de La Laguna
    info

    Universidad de La Laguna

    San Cristobal de La Laguna, España

    ROR https://ror.org/01r9z8p25

Proceedings:
The Automatic Speaker Verification Spoofing Countermeasures Workshop (ASVspoof 2024)

Year of publication: 2024

Pages: 144-151

Type: Conference paper

DOI: 10.21437/ASVSPOOF.2024-21 GOOGLE SCHOLAR lock_openOpen access editor

Sustainable development goals

Abstract

This paper presents the work carried out by the ASASVIcomtech team, made up of researchers from Vicomtech and University of Granada, for the ASVspoof5 Challenge. The team has participated in both Track 1 (speech deepfake detection) and Track 2 (spoofing-aware speaker verification). This work started with an analysis of the challenge available data, which was regarded as an essential step to avoid later potential biases of the trained models, and whose main conclusions are presented here. With respect to the proposed approaches, a closed-condition system employing a deep complex convolutional recurrent architecture was developed for Track 1, although, unfortunately, no noteworthy results were achieved. On the other hand, different possibilities of open-condition systems, based on leveraging self-supervised models, augmented training data from previous challenges, and novel vocoders, were explored for both tracks, finally achieving very competitive results with an ensemble system