Transformers
PyTorch
wav2vec2
pretraining
mms
Inference Endpoints

Massively Multilingual Speech (MMS) - 300m

Facebook's MMS counting 300m parameters.

MMS is Facebook AI's massive multilingual pretrained model for speech ("MMS"). It is pretrained in with Wav2Vec2's self-supervised training objective on about 500,000 hours of speech data in over 1,400 languages.

When using the model make sure that your speech input is sampled at 16kHz.

Note: This model should be fine-tuned on a downstream task, like Automatic Speech Recognition, Translation, or Classification. Check out the **How-to-fine section or this blog for more information about ASR.

Table Of Content

How to finetune

Coming soon...

Model details

  • Developed by: Vineel Pratap et al.

  • Model type: Multi-Lingual Automatic Speech Recognition model

  • Language(s): 1000+ languages

  • License: CC-BY-NC 4.0 license

  • Num parameters: 300 million

  • Cite as:

    @article{pratap2023mms,
      title={Scaling Speech Technology to 1,000+ Languages},
      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},
    journal={arXiv},
    year={2023}
    }
    

Additional Links

Downloads last month
26,780
Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for facebook/mms-300m

Finetunes
12 models
Quantizations
1 model

Dataset used to train facebook/mms-300m

Spaces using facebook/mms-300m 13