# 16kHz sampling rate adaptation

An Italian automatic speech recognition model fine-tuned from facebook/wav2vec2-large-fr-voxpopuli, trained using the Common Voice 7.0 Italian dataset

An Italian automatic speech recognition model fine-tuned based on microsoft/wavlm-large, trained using the Common Voice 7.0 Italian dataset.

A speech recognition model fine-tuned on the Arabic Common Voice dataset based on facebook/wav2vec2-large-xlsr-53

This model is a fine-tuned version of Facebook's Wav2Vec2, specializing in speech recognition tasks. It was pre-trained on various speech data and fine-tuned on Librispeech, featuring strong robustness.

Tamil automatic speech recognition (ASR) model fine-tuned from facebook/wav2vec2-large-xlsr-53

A speech recognition model fine-tuned on the Basque language (Euskera) using the Common Voice dataset, based on the facebook/wav2vec2-large-xlsr-53 model.

An automatic speech recognition model fine-tuned on Ukrainian using the Common Voice dataset, based on facebook/wav2vec2-large-xlsr-53

An Arabic speech recognition model fine-tuned on the Arabic speech corpus dataset, based on the facebook/wav2vec2-large-xlsr-53 model

Automatic speech recognition model fine-tuned on Estonian Common Voice dataset based on facebook/wav2vec2-large-xlsr-53

An Arabic automatic speech recognition model fine-tuned based on facebook/wav2vec2-large-xlsr-53, achieving a WER of 52% on the Common Voice Arabic dataset.

A Punjabi automatic speech recognition model fine-tuned based on the CLSRIL-23 multilingual pretrained model, supporting 16kHz sampled speech input.

Tamil automatic speech recognition model based on Wav2Vec2 architecture, developed by Harveen Chadha, fine-tuned on 4200 hours of Hindi data

A Swedish speech recognition model fine-tuned using NST and Common Voice data, based on Facebook's VoxPopuli-sv base model.