Massively Multilingual Speech (MMS) Finetuned ASR ALL This checkpoint is a model fine tuned for multi lingual ASR and part of Facebook's Massive Multilingual Speech project. This checkpoint is based on the Wav2Vec2 architecture and makes use of adapter models to transcribe 1000+ languages. The checkpoint consists of 1 billion parameters and has been fine tuned from facebook/mms 1b on 1162 languages. Table Of Content Example Supported Languages Model details Additional links Example This MMS checkpoint can be used with Transformers to transcribe audio of 1107 different languages. Let's look at a simple example. First, we install transformers and some other libraries Note : In order to use MMS you need to have at least transformers = 4.30 installed. If the 4.30 version is not yet available on PyPI make sure to install transformers from source: Next, we load a couple of audio samples via datasets . Make sure that the audio data is sampled to 16000 kHz. Next, we load the model and processor Now we process the audio data, pass the processed audio data to the model and transcribe the model output, just like we usually do for Wav2Vec2 models such as facebook/wav2vec2 base 960h We can now…
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