# XLSR Fine-tuning

Chinese speech recognition model fine-tuned based on XLSR-53 large model, supporting 16kHz sampled audio input

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

Optimized automatic speech recognition model for Galician, fine-tuned based on wav2vec2-large-xlsr-53, with a WER of 7.12

An automatic speech recognition model fine-tuned on the English Common Voice dataset based on facebook/wav2vec2-large-xlsr-53, supporting English speech input at 16kHz sampling rate.

An automatic speech recognition (ASR) model fine-tuned on the Persian Common Voice dataset based on Facebook's wav2vec2-large-xlsr-53 model

An automatic speech recognition model fine-tuned on the Common Voice German dataset based on facebook/wav2vec2-large-xlsr-53, achieving a test WER of 15.80%.

A Cantonese speech recognition model fine-tuned based on Facebook's wav2vec2-large-xlsr-53 model, supporting 16kHz sampled audio input.

This is a Turkish automatic speech recognition model based on the XLSR Wav2Vec2 architecture, fine-tuned on the Common Voice Turkish dataset.

This is an Indonesian automatic speech recognition model based on the XLSR Wav2Vec2 architecture, developed by cahya and fine-tuned on the Common Voice Indonesian dataset.

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

This is an Indonesian speech recognition model fine-tuned based on facebook/wav2vec2-large-xlsr-53, trained on the Common Voice Indonesian dataset.

A Bengali automatic speech recognition model fine-tuned based on facebook/wav2vec2-large-xlsr-53, trained using OpenSLR dataset.

This is a multilingual automatic speech recognition (ASR) model supporting 56 languages, fine-tuned from facebook/wav2vec2-large-xlsr-53 on the Common Voice dataset.

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

A Fon speech recognition model fine-tuned from facebook/wav2vec2-large-xlsr-53, achieving a test WER of 14.97%

A speech recognition model fine-tuned on the German Common Voice dataset based on facebook/wav2vec2-large-xlsr-53, with a word error rate of 29.35%

A Japanese automatic speech recognition model fine-tuned from facebook/wav2vec2-large-xlsr-53 using the Common Voice and JSUT datasets.

This is an automatic speech recognition (ASR) model fine-tuned on the Common Voice 7.0 Thai dataset based on the wav2vec2-large-xlsr-53 model.

This is an automatic speech recognition (ASR) model fine-tuned on the Interlingua language using Facebook's wav2vec2-large-xlsr-53 model, trained on the Common Voice dataset.

A fine-tuned model based on facebook/wav2vec2-large-xlsr-53 for Japanese speech recognition tasks.

A Hindi speech recognition model fine-tuned from facebook/wav2vec2-large-xlsr-53, trained using OpenSLR and Common Voice Hindi datasets, supporting 16kHz sampling rate audio input.

This is a German automatic speech recognition model based on the XLSR Wav2Vec2 architecture with language model support, excelling on the Common Voice German dataset.

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

This is an automatic speech recognition model fine-tuned on Gujarati based on facebook/wav2vec2-large-xlsr-53, with a test WER of 28.92%.

A Chinese (zh-CN) speech recognition model fine-tuned on the Common Voice dataset based on facebook/wav2vec2-large-xlsr-53

Hindi speech recognition model fine-tuned on the common_voice dataset based on facebook/wav2vec2-large-xlsr-53