
In the new paper Mu²SLAM: Multitask, Multilingual Speech and Language Models, the Google researchers present Mu2SLAM, a multilingual sequence-to-sequence pretraining method for speech and text models that covers arbitrary tasks in over 100 languages and achieves state-of-the-art translation performance on the CoVoST benchmark. Mu²SLAM is based on an encoder-decoder backbone model and is jointly pretrained on four different data types: speech-only, text-onl












