# VietPrism: A large-scale Vietnamese speech and deepfake corpus with diverse dialects and code-switching

arXiv: https://arxiv.org/abs/2609.30005 · HTML: https://mlsanity.com/paper/2609.30005/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 11 of its 15 references that are in the map.
- First posted on arXiv 24 Sep 2026.

## Builds on (most cited first, 11 of 11)

- [Common Voice: A Massively-Multilingual Speech Corpus](https://mlsanity.com/paper/1912.06670/) (2019)
- [Qwen3-Omni Technical Report](https://mlsanity.com/paper/2509.17765/) (2025)
- [GigaSpeech 2: An Evolving, Large-Scale and Multi-domain ASR Corpus for Low-Resource Languages with Automated Crawling, Transcription and Refinement](https://mlsanity.com/paper/2406.11546/) (2024)
- [DeepFilterNet2: Towards Real-Time Speech Enhancement on Embedded Devices for Full-Band Audio](https://mlsanity.com/paper/2205.05474/) (2022)
- [Data Quality Issues in Multilingual Speech Datasets: The Need for Sociolinguistic Awareness and Proactive Language Planning](https://mlsanity.com/paper/2506.17525/) (2025)
- [ClearerVoice-Studio: Bridging Advanced Speech Processing Research and Practical Deployment](https://mlsanity.com/paper/2506.19398/) (2025)
- [Post-training for Deepfake Speech Detection](https://mlsanity.com/paper/2506.21090/) (2025)
- [Do Compact SSL Backbones Matter for Audio Deepfake Detection? A Controlled Study with RAPTOR](https://mlsanity.com/paper/2603.06164/) (2026)
- [VoxVietnam: a Large-Scale Multi-Genre Dataset for Vietnamese Speaker Recognition](https://mlsanity.com/paper/2501.00328/) (2024)
- [ViMedCSS: A Vietnamese Medical Code-Switching Speech Dataset & Benchmark](https://mlsanity.com/paper/2602.12911/) (2026)
- [OpenBibleTTS: Large-Scale Speech Resources and TTS Models for Low-Resource Languages](https://mlsanity.com/paper/2606.09553/) (2026)

## Abstract (arXiv)

Vietnamese speech research is constrained by resources that isolate automatic speech recognition from speaker, dialect, code-switching, and deepfake analysis. We introduce VietPrism, an open, multi-domain corpus that brings these dimensions together at scale: 993.4 hours and 403,941 bona fide utterances from 1,262 verified speakers across 8,388 real-world videos. To our knowledge, it is the first large-scale Vietnamese corpus to jointly provide transcripts, consistent speaker identities, five dialect groups, and naturally occurring Vietnamese--English code-switching, which constitutes nearly half of the corpus by duration. We further create over 3.1K hours of spoof speech with four open-source and commercial synthesis systems. Every spoof is conditioned on a verified speaker reference and paired with a transcript- and speaker-matched bona fide utterance, enabling unique controlled evaluation with reduced lexical and identity confounds. Zero-shot evaluation of five pretrained multilingual detectors reveals striking brittleness: EER greatly varies across detector--generator pairings, while recent multilingual detector DFA-1B degrades from 16.3% to 33.6% as speaker similarity increases. Dialect-stratified results expose further model-dependent disparities. By unifying natural linguistic diversity with controlled spoof generation, VietPrism provides a challenging foundation for Vietnamese speech modeling and trustworthy audio-deepfake detection.