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1961afd 5d76915 1961afd 5d76915 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | # SynthVoice: This should be a paper Title
📑 [Paper](https://huggingface.co/papers/xxxx.xxxxx) | 🌐 [Project Page](https://synthvoice.github.io/) | 💾 [Released Resources](https://huggingface.co/collections/toolevalxm/synthvoice-67a978e28fd926b56a4f55a2) | 📦 [Repo](https://github.com/xmhtoolathlon/Annoy-DataSync)
This is the resource page of our SynthVoice collection on Huggingface.
**Dataset**
| Dataset | Link |
|-|-|
| SynthVoice-Processed | [🤗](https://huggingface.co/datasets/toolevalxm/SynthVoice-Processed) |
Please also check the raw data: [toolevalxm/SynthVoice-Raw](https://huggingface.co/datasets/toolevalxm/SynthVoice-Raw).
**Models**
| Base Model / Training | SynthVoice | SynthVoice++ |
|-|-|-|
| Coqui TTS VITS | [🤗](https://huggingface.co/toolevalxm/synthvoice-vits) | [🤗](https://huggingface.co/toolevalxm/synthvoice-vits-pp) |
**Introduction**
We utilize the Coqui TTS framework for synthesizing high-quality voice outputs from text transcripts. The synthesis is performed using the VITS model architecture, which has demonstrated superior quality in text-to-speech generation tasks. Our approach involves:
1. Processing raw LibriSpeech transcripts
2. Using Coqui TTS (coqui-ai/TTS) for voice synthesis
3. Post-processing and quality filtering
*Due to licensing requirements, we only release the processed subset containing synthesized outputs.
**License**
The license for this dataset is CC BY 4.0. |