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--- |
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license: cc-by-nc-4.0 |
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tags: |
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- mms |
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- vits |
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pipeline_tag: text-to-speech |
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--- |
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# Massively Multilingual Speech (MMS) : Text-to-Speech Models |
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This repository contains the **Ayta, Abellen (abp)** language text-to-speech (TTS) model checkpoint. |
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This model is part of Facebook's [Massively Multilingual Speech](https://arxiv.org/abs/2305.13516) project, aiming to |
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provide speech technology across a diverse range of languages. You can find more details about the supported languages |
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and their ISO 639-3 codes in the [MMS Language Coverage |
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Overview](https://dl.fbaipublicfiles.com/mms/misc/language_coverage_mms.html). |
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## Usage |
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Using this checkpoint from Hugging Face Transformers: |
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```python |
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from transformers import VitsModel, VitsMmsTokenizer |
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import torch |
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model = VitsModel.from_pretrained("Matthijs/mms-tts-abp") |
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tokenizer = VitsMmsTokenizer.from_pretrained("Matthijs/mms-tts-abp") |
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text = "some example text in the Ayta, Abellen language" |
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inputs = tokenizer(text, return_tensors="pt") |
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with torch.no_grad(): |
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output = model(**inputs) |
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from IPython.display import Audio |
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Audio(output.audio[0], rate=16000) |
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``` |
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Note: For certain checkpoints, the input text must be converted to the Latin alphabet first using the |
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[uroman](https://github.com/isi-nlp/uroman) tool. |
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## Model credits |
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This model was developed by Vineel Pratap et al. and is licensed as **CC-BY-NC 4.0** |
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@article{pratap2023mms, |
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title={Scaling Speech Technology to 1,000+ Languages}, |
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author={Vineel Pratap and Andros Tjandra and Bowen Shi and Paden Tomasello and Arun Babu and Sayani Kundu and Ali Elkahky and Zhaoheng Ni and Apoorv Vyas and Maryam Fazel-Zarandi and Alexei Baevski and Yossi Adi and Xiaohui Zhang and Wei-Ning Hsu and Alexis Conneau and Michael Auli}, |
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journal={arXiv}, |
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year={2023} |
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} |
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