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@@ -5,8 +5,64 @@ tags:
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  - fairseq
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  - audio
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  - text-to-speech
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- language: en
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  datasets:
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- - ljspeech
 
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  ---
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- ## Example
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - fairseq
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  - audio
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  - text-to-speech
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+ language: fr
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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-fr-cv7_css10
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+
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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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+ - French
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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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+
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+ ## Usage
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+
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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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+
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+
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+ models, cfg, task = load_model_ensemble_and_task_from_hf_hub(
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+ "facebook/tts_transformer-fr-cv7_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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+
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+ text = "Hello, this is a test run."
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+
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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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+
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+ ipd.Audio(wav, rate=rate)
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+ ```
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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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+
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+ ## Citation
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+
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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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+ ```