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Dolly-Audio: Vietnamese Multi-Speaker High-Quality Speech Corpus
Dataset Summary
Dolly-Audio is a large-scale, high-quality Vietnamese speech corpus created by the Dolly AI Team. Inspired by Dolly, the world’s first cloned mammal, the project aims to advance research in Vietnamese speech synthesis, speech recognition, and voice modeling.
This release provides nearly 1,000 hours of professionally cleaned audio, featuring 152 speakers across different Vietnamese regions and speaking styles. Text transcripts span a wide variety of domains to ensure linguistic diversity and model robustness.
Key Features
- ~1,000 hours of high-quality Vietnamese speech
- 152 multi-region speakers with diverse accents
- Cleaned, noise-free audio; no background music
- Sentence-level boundary trimming for natural prosody
- Rich transcript domains (news, entertainment, education, conversational, etc.)
- Estimated near-zero WER (≈ 0%) from manual sampling
- Suitable for TTS, ASR, voice cloning, and speech research
Intended Use
The dataset is ideal for:
- Multi-speaker text-to-speech (TTS)
- Automatic speech recognition (ASR)
- Voice cloning and speaker adaptation
- Prosody modeling
- Linguistic and phonetic research
Commercial use is not permitted under the license.
Usage Restrictions
- Non-commercial research use only
- Redistribution must comply with CC-BY-NC-SA-4.0
- Users must verify dataset suitability for their research task
- Institutional email required for access approval
Citation
If you use Dolly-Audio in your research, please credit the creators:
Nguyen Vinh Huy — nguyenvinhhuy@dtu.edu.vn Nguyen Dinh Thuan — boyphuthien115@gmail.com
@dataset{dolly_audio_2025, title = {Dolly-Audio: Vietnamese Multi-Speaker High-Quality Speech Corpus}, author = {Nguyen, Vinh Huy and Nguyen, Dinh Thuan}, year = {2025}, publisher = {Dolly AI Team}, howpublished = {\url{https://huggingface.co/datasets/Dolly-AI/Dolly-Audio}}, note = {Released under CC-BY-NC-SA-4.0. Research use only.} }
Contact
For access requests or inquiries, please contact the maintainers via the emails above.
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