# Multilingual speech processing

Uzbek speech recognition model fine-tuned on Whisper Base, trained on the Common Voice dataset

This model is a speech recognition model fine-tuned on the Common Voice Turkish dataset based on facebook/wav2vec2-large-xlsr-53

This is a speech recognition model fine-tuned on the Common Voice Irish dataset based on the facebook/wav2vec2-xls-r-300m model, primarily used for automatic speech recognition tasks in Irish.

This model is an automatic speech recognition model fine-tuned on the Abkhaz language dataset, based on the XLS-R architecture

This is an automatic speech recognition model fine-tuned from the facebook/wav2vec2-large-xlsr-53 model, specifically designed for recognizing the Sursilvan dialect of Romansh.

This is a Slovenian speech recognition model fine-tuned from Facebook's wav2vec2-large-xlsr-53 model, trained using the Common Voice dataset.

This is an automatic speech recognition model fine-tuned on the Welsh dataset based on facebook/wav2vec2-xls-r-300m, achieving a word error rate of 31.003% and a character error rate of 7.775% on the Common Voice 7 Welsh test set.

This model is an automatic speech recognition model fine-tuned on Estonian datasets based on facebook/wav2vec2-xls-r-1b

A speech recognition model based on Facebook's Wav2Vec2 architecture, pretrained on the VoxPopuli corpus and fine-tuned on Croatian data

Facebook's Wav2Vec2 large model, pretrained exclusively on 66.3 hours of unlabeled data from the West Germanic VoxPopuli corpus.

Greek speech recognition model pretrained on VoxPopuli corpus using 17.7 hours of unlabeled data

Large speech model pre-trained on North Germanic language corpus from VoxPopuli

This model is a Turkish speech recognition model fine-tuned on common speech datasets based on facebook/wav2vec2-xls-r-300m