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README.md
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- fairseq
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- audio
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- text-to-speech
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language:
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datasets:
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---
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- fairseq
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- audio
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- text-to-speech
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language: ru
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datasets:
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- common_voice
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- css10
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---
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# tts_transformer-ru-css10
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[Transformer](https://arxiv.org/abs/1809.08895) text-to-speech model from fairseq S^2 ([paper](https://arxiv.org/abs/2109.06912)/[code](https://github.com/pytorch/fairseq/tree/main/examples/speech_synthesis)):
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- Russian
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- Single-speaker male voice
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- Pre-trained on [Common Voice v7](https://commonvoice.mozilla.org/en/datasets), fine-tuned on [CSS10](https://github.com/Kyubyong/css10)
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## Usage
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```python
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from fairseq.checkpoint_utils import load_model_ensemble_and_task_from_hf_hub
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from fairseq.models.text_to_speech.hub_interface import TTSHubInterface
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import IPython.display as ipd
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models, cfg, task = load_model_ensemble_and_task_from_hf_hub(
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"facebook/tts_transformer-es-css10",
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arg_overrides={"vocoder": "hifigan", "fp16": False}
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)
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model = models[0]
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TTSHubInterface.update_cfg_with_data_cfg(cfg, task.data_cfg)
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generator = task.build_generator(model, cfg)
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text = "Hello, this is a test run."
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sample = TTSHubInterface.get_model_input(task, text)
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wav, rate = TTSHubInterface.get_prediction(task, model, generator, sample)
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ipd.Audio(wav, rate=rate)
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```
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See also [fairseq S^2 example](https://github.com/pytorch/fairseq/blob/main/examples/speech_synthesis/docs/common_voice_example.md).
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## Citation
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```bibtex
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@inproceedings{wang-etal-2021-fairseq,
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title = "fairseq S{\^{}}2: A Scalable and Integrable Speech Synthesis Toolkit",
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author = "Wang, Changhan and
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Hsu, Wei-Ning and
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Adi, Yossi and
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Polyak, Adam and
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Lee, Ann and
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Chen, Peng-Jen and
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Gu, Jiatao and
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Pino, Juan",
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booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
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month = nov,
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year = "2021",
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address = "Online and Punta Cana, Dominican Republic",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2021.emnlp-demo.17",
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doi = "10.18653/v1/2021.emnlp-demo.17",
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pages = "143--152",
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}
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```
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