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fnooub/dolly-audio-1000h-vietnamese

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Hugging Face2026-03-21 更新2026-03-29 收录
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--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: audio_filename dtype: string - name: text dtype: string - name: voice_id dtype: string - name: audio dtype: audio: decode: false splits: - name: train num_bytes: 165955597080 num_examples: 664125 download_size: 157800059320 dataset_size: 165955597080 language: - vi tags: - vietnamese - synthetic - audio - tts size_categories: - 100K<n<1M --- # *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](mailto:nguyenvinhhuy@dtu.edu.vn) *Nguyen Dinh Thuan* — [boyphuthien115@gmail.com](mailto: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.

configs: - 配置名称:default 数据文件: - 拆分集:训练集 路径:data/train-* dataset_info: 特征: - 字段名:audio_filename,数据类型:字符串 - 字段名:text,数据类型:字符串 - 字段名:voice_id,数据类型:字符串 - 字段名:audio,数据类型: 音频: 解码:否 拆分集: - 名称:训练集,总字节数:165955597080,样本数量:664125 下载大小:157800059320 数据集总大小:165955597080 语言: - 越南语 tags: - 越南语 - 合成数据 - 音频 - 文本转语音(Text-to-Speech, TTS) size_categories: - 10万 < 样本数 < 100万 --- # *Dolly-Audio:越南语多说话人高质量语音语料库* ## *数据集概述* *Dolly-Audio* 是由 *Dolly AI团队* 打造的大规模高质量越南语语音语料库。本项目得名于世界首只克隆哺乳动物多莉,旨在推动越南语语音合成、语音识别与说话人建模领域的研究。 本次发布的语料包含近1000小时经专业清洗的音频数据,涵盖越南各地区的152名说话人,且包含多元说话风格。文本转录覆盖多元领域,以确保语言多样性与模型鲁棒性。 --- ## *核心特性* * 近1000小时高质量越南语语音数据 * 152名覆盖越南各地区、口音与说话风格多元的多说话人 * 经专业清洗的无噪音频,无背景音乐干扰 * 针对自然韵律完成句级边界裁剪 * 丰富的转录文本领域(涵盖新闻、娱乐、教育、会话等场景) * 经人工抽样估算,词错误率(Word Error Rate, WER)接近0(≈0%) * 适用于文本转语音(TTS)、自动语音识别(ASR)、说话人克隆及语音相关研究 --- ## *预期用途* 本数据集适用于: * 多说话人文本转语音(TTS) * 自动语音识别(ASR) * 说话人克隆与说话人适配 * 韵律建模 * 语言学与语音学研究 根据许可协议,商业使用不被允许。 --- ## *使用限制* * 仅可用于非商业性研究用途 * 重新分发需遵守 *CC-BY-NC-SA-4.0* 协议 * 用户需自行验证数据集是否适配自身研究任务 * 申请访问需提供机构邮箱以完成审批 --- ## *引用方式* 若您在研究中使用*Dolly-Audio*,请引用如下创作者: *阮文惠(Nguyen Vinh Huy)* — [nguyenvinhhuy@dtu.edu.vn](mailto:nguyenvinhhuy@dtu.edu.vn) *阮丁顺(Nguyen Dinh Thuan)* — [boyphuthien115@gmail.com](mailto:boyphuthien115@gmail.com) bibtex @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.} } --- ## *联系方式* 如需申请访问或咨询,请通过上述邮箱与维护者联系。
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