facebook/wav2vec2-large-xlsr-53

The base model pretrained on 16kHz sampled speech audio . When using the model make sure that your speech input is also sampled at 16Khz . Note that this model should be fine-tuned on a downstream task, like Automatic Speech Recognition . XLSR shows a relative phoneme error rate reduction of 72% compared to the best known results . On BABEL, our approach improves word error rate by 16% relative compared to a comparable system . We hope to catalyze research in low-resource speech understanding by releasing a large model pretraining in 53 languages . The original model can be found under https://github.com/pytorch/fairseq/tree/master,