mlsanityData to 14 Oct 2026

The DKU-DUKEECE System for the Manipulation Region Location Task of ADD 2023

arXiv 2308.10281 ↗First posted 20 Aug 2023eess.AS cs.AI cs.LGcited by 1

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Abstract (arXiv)

This paper introduces our system designed for Track 2, which focuses on locating manipulated regions, in the second Audio Deepfake Detection Challenge (ADD 2023). Our approach involves the utilization of multiple detection systems to identify splicing regions and determine their authenticity. Specifically, we train and integrate two frame-level systems: one for boundary detection and the other for deepfake detection. Additionally, we employ a third VAE model trained exclusively on genuine data to determine the authenticity of a given audio clip. Through the fusion of these three systems, our top-performing solution for the ADD challenge achieves an impressive 82.23% sentence accuracy and an F1 score of 60.66%. This results in a final ADD score of 0.6713, securing the first rank in Track 2 of ADD 2023.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 12 of its 20 references that are in the map. First posted on arXiv 20 Aug 2023.

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12 of 20 references.

References · 12

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  1. 2024Speech-Forensics: Towards Comprehensive Synthetic Speech Dataset Establishment and Analysiscited by 5