VSASV: a Vietnamese Dataset for Spoofing-Aware Speaker Verification

Recent research in improving speaker verification systems to detect spoofed speech has seen a concentrated focus on English language, while the performance of such systems in other languages remains unexplored. This paper introduces the VSASV dataset for Spoofing-Aware Speaker Verification (SASV) in Vietnamese language. The dataset comprises over 174,000 spoofed utterances and 164,000 authentic utterances from 1,382 speakers, which were generated with the latest spoofing techniques to encourage the development of SASV systems in this language. We also provide experimental results on the efficacy of the different state-of-the-art anti-spoofing systems on Vietnamese language.