Wav2Vec2-Large-XLSR-53 The base model pretrained and fine-tuned on 960 hours of Librispeech on 16kHz sampled speech audio. When using the model make sure that your speech input is also sampled at 16Khz. More Info Meta AI Research post:Wav2vec 2.0: Learning the structure of speech from...
October 2021Released multilingual finetuned XLSR-53 model September 2021masterbranch renamed tomain. July 2021Released DrNMT code July 2021Released Robust wav2vec 2.0 model June 2021Released XLMR-XL and XLMR-XXL models May 2021Released Unsupervised Speech Recognition code ...
We also release multilingual pre-trained wav2vec 2.0 (XLSR) models: ModelArchitectureHoursLanguagesDatasetsModel XLSR-53Large56k53MLS, CommonVoice, BABELdownload The XLSR model uses the following datasets for multilingual pretraining: MLS: Multilingual LibriSpeech(8 languages, 50.7k hours):Dutch, Eng...
To evaluate cross-linguality, we trained wav2vec 2.0 on unannotated speech audio of 12 languages from the Common Voice benchmark. The resulting approach, called XLSR, shows that cross-lingual training dramatically improves performance on low-resource languages, compared with training only on a sing...
wav2vec 2.0 We provide pre-trained wav2vec 2.0 models (implemented infairseqandwav2letter/flashlight) for downstream speech tasks. Each language is covered by a monolingualBasemodel and multilingualLargemodels that combine languages in the same family or all languages. See alsoXLS-Rfor larger-scal...
October 2021 Released multilingual finetuned XLSR-53 model September 2021 master branch renamed to main. July 2021 Released DrNMT code July 2021 Released Robust wav2vec 2.0 model June 2021 Released XLMR-XL and XLMR-XXL models May 2021 Released Unsupervised Speech Recognition code March 2021 Adde...
For large datasets install PyArrow: pip install pyarrow If you use Docker make sure to increase the shared memory size either with --ipc=host or --shm-size as command line options to nvidia-docker run .Getting StartedThe full documentation contains instructions for getting started, training new...
For large datasets install PyArrow: pip install pyarrow If you use Docker make sure to increase the shared memory size either with --ipc=host or --shm-size as command line options to nvidia-docker run .Getting StartedThe full documentation contains instructions for getting started, training new...
For large datasets install PyArrow: pip install pyarrow If you use Docker make sure to increase the shared memory size either with --ipc=host or --shm-size as command line options to nvidia-docker run .Getting StartedThe full documentation contains instructions for getting started, training new...
wav2vec: Unsupervised Pre-training for Speech Recognition (Schneider et al., 2019) LightConv and DynamicConv models Pay Less Attention with Lightweight and Dynamic Convolutions (Wu et al., 2019) Long Short-Term Memory (LSTM) networks