HighQuality-TTS
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https://modelscope.cn/datasets/Kratos-AI/HighQuality-TTS
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# High-Quality TTS Speech Dataset
This dataset contains clean, high-quality human-recorded speech clips under studio environment designed for **neural Text-to-Speech (TTS)** model training. Each recording is captured in a quiet environment with clear pronunciation and consistent pacing.
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## Dataset Features
- Studio-quality microphone recordings
- Minimal background noise
- Consistent tone, pacing, and speaking style
- Suitable for both research and commercial TTS modeling with attribution
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## Intended Uses
### ✅ Direct Use
- Training neural Text-to-Speech (TTS) models
- Benchmarking voice synthesis quality
- Prosody and voice-style modeling
- Multilingual and accent adaptation research
- Phoneme, grapheme, and linguistic modeling
### ❌ Out-of-Scope Use
- Real-time, mission-critical speech systems
- Medical or diagnostic speech analysis
- Commercial deployment without proper CC BY 4.0 credit
- Biometric or individual identity recognition
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## Considerations and Limitations
- ❗ Dataset size is limited (<1,000 samples) and may not cover all phonetic diversity
- 🎧 Voice style is consistent; may not generalize to diverse accents or emotional variations
- 🔄 Future expansions will include more speakers, accents, and emotions for better generalization
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## License
**CC BY 4.0** — Free to use, modify, distribute, and publish with attribution.
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## Contact
For dataset collaboration, contribution, or citation details, contact:
- anoushka@kgen.io
- abhishek.vadapalli@kgen.io
# 高质量文本转语音(TTS)数据集
本数据集收录了工作室环境下录制的清晰、高品质人声语音片段,专为**神经文本转语音(Text-to-Speech, TTS)**模型训练打造。所有录音均采集于安静环境,发音清晰、节奏均匀。
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## 数据集特性
- 专业工作室级麦克风录音
- 背景噪音极低
- 音调、节奏与说话风格保持一致
- 可用于学术研究与商用TTS模型构建,需标注来源
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## 适用场景
### ✅ 直接适用场景
- 神经文本转语音(TTS)模型训练
- 语音合成质量基准测试
- 韵律与语音风格建模
- 多语言与口音适配研究
- 音素、字素与语言建模
### ❌ 不适用场景
- 实时关键任务语音系统
- 医疗或诊断性语音分析
- 未按要求标注CC BY 4.0许可的商用部署
- 生物识别或个人身份识别
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## 注意事项与局限性
- ❗ 数据集规模有限(样本量不足1000条),无法覆盖所有语音多样性
- 🎧 语音风格单一,难以适配多样化口音或情感表达
- 🔄 未来将扩展收录更多发言人、口音与情感样本,以提升泛化能力
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## 许可协议
**CC BY 4.0** — 允许在注明来源的前提下免费使用、修改、分发与发布。
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## 联系方式
如需开展数据集合作、贡献内容或获取引用详情,请联系:
- anoushka@kgen.io
- abhishek.vadapalli@kgen.io
提供机构:
maas
创建时间:
2025-11-25



