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README.md
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- **Duration Range:** 2.4s - 16.3s
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- **Avg Text Length:** 142 characters
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## Usage
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This dataset is optimized for:
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- **Text-to-Speech (TTS) Fine-tuning** with models like Orpheus-TTS
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- **Voice Conversion (VC)** experiments with kNN-VC and similar methods
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- **Hybrid TTS+VC** pipeline development
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- **ASR Evaluation** on pathological speech
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- **Speech Synthesis Research** for accessibility applications
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### Loading the Dataset
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# ... other trainer arguments
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## Research Applications
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This dataset is part of a larger study on pathological speech synthesis and ASR degradation, investigating:
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1. **TTS Fine-tuning**: Speaker-specific fine-tuning of large TTS models
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2. **Voice Conversion**: Zero-shot conversion from healthy to pathological speech
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3. **Hybrid Approaches**: Combining TTS content generation with VC-based acoustic styling
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4. **ASR Robustness**: Evaluating ASR performance on synthetic pathological speech
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## Citation
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If you use this dataset in your research, please cite:
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```bibtex
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@dataset{librispeech_female_2025,
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title={Librispeech Female Dataset for Pathological Speech Synthesis},
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author={Your Name},
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year={2025},
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publisher={Hugging Face},
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url={https://huggingface.co/datasets/your-username/librispeech_female}
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}
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```
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## Original Corpus Citation
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**LibriSpeech Corpus:**
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- TORGO: Please cite the original TORGO database papers
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- UA-Speech: Please cite the original UA-Speech corpus papers
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- LibriSpeech: Please cite the original LibriSpeech papers
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## License
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MIT License - See LICENSE file for details.
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## Ethical Considerations
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This dataset contains speech from individuals with speech disorders and should be used responsibly:
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- Respect speaker privacy and dignity
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- Use for legitimate research purposes
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- Consider potential biases in synthetic speech generation
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- Ensure accessibility improvements benefit the target communities
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## Contact
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For questions about this dataset or the associated research, please contact [your-email].
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- **Duration Range:** 2.4s - 16.3s
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- **Avg Text Length:** 142 characters
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### Loading the Dataset
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# ... other trainer arguments
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)
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```
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