# Low-resource language ASR

A fine-tuned version of OpenAI's Whisper model, specifically designed for automatic speech recognition tasks in the low-resource Ghanaian language Akan

An Arabic (Tunisian dialect) speech recognition model fine-tuned on the AT_ENT dataset based on openai/whisper-medium

A speech recognition model fine-tuned on Darija dialect speech-to-text dataset based on openai/whisper-medium

Amharic speech recognition model fine-tuned on the common_voice_16_1 dataset based on facebook/wav2vec2-xls-r-300m

Kyrgyz Whisper ASR is a customized automatic speech recognition solution specifically designed for the Kyrgyz language, fine-tuned based on the pre-trained Whisper model.

Kyrgyz automatic speech recognition (ASR) model based on the Whisper architecture, developed with support from the National Commission on Language and Language Policy under the President of the Kyrgyz Republic

A Pashto (ps) speech recognition model fine-tuned based on OpenAI Whisper-small, trained on the FLEURS dataset

This is an automatic speech recognition model for the Moroccan Arabic dialect (Darija), fine-tuned on the DVoice dataset based on the wav2vec 2.0 architecture.

This is an Urdu automatic speech recognition (ASR) model based on the wav2vec2 architecture, trained from scratch.

This is an automatic speech recognition (ASR) model fine-tuned on the Common Voice 8.0 dataset based on the facebook/wav2vec2-xls-r-300m model, specifically optimized for the Guarani language (gn).

A Hakha Chin speech recognition model fine-tuned from the facebook/wav2vec2-large-xlsr-53 model, trained on the Common Voice dataset with a test WER of 31.38%.

An automatic speech recognition (ASR) model fine-tuned on the Guarani (gn) Common Voice 8.0 dataset based on the facebook/wav2vec2-xls-r-300m model

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

A Telugu speech recognition model fine-tuned based on the facebook/wav2vec2-large-xlsr-53 model, trained using the OpenSLR SLR66 dataset

This is an automatic speech recognition (ASR) model fine-tuned on Kurmanji Kurdish datasets based on facebook/wav2vec2-xls-r-300m.

A fine-tuned automatic speech recognition model for Persian (Farsi) based on facebook/wav2vec2-large-xlsr-53, supporting 16kHz sampled audio input.

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the Common Voice dataset for Abkhaz automatic speech recognition tasks.

Automatic speech recognition model fine-tuned on Yakut (SAH) dataset based on facebook/wav2vec2-xls-r-300m

This is a Wolof automatic speech recognition model fine-tuned based on facebook/wav2vec2-xls-r-300m, aimed at addressing the scarcity of Wolof language resources.

This is an automatic speech recognition (ASR) model fine-tuned on Kannada language using Facebook's wav2vec2-large-xlsr-53 model, trained with the OpenSLR SLR79 dataset.

An automatic speech recognition model fine-tuned on Dhivehi data from Common Voice, based on the facebook/wav2vec2-large-xlsr-53 model.

This is a Marathi automatic speech recognition (ASR) model fine-tuned from facebook/wav2vec2-large-xlsr-53, trained using OpenSLR and InterSpeech 2021 datasets.

A Dhivehi automatic speech recognition model fine-tuned from facebook/wav2vec2-large-xlsr-53, achieving a Word Error Rate (WER) of 32.85%.

Fine-tuned Odia automatic speech recognition model based on facebook/wav2vec2-large-xlsr-53, trained using Low Resource Indian Language Challenge data

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

This is an automatic speech recognition (ASR) model fine-tuned on Kyrgyz speech datasets based on the facebook/wav2vec2-xls-r-300m model

This is an automatic speech recognition model fine-tuned on the Common Voice Abkhaz (ab) dataset based on the XLS-R architecture

This is an automatic speech recognition model fine-tuned on the Punjabi (India) dataset based on the facebook/wav2vec2-xls-r-300m model.

This model is an automatic speech recognition model fine-tuned on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - GN dataset based on Facebook's wav2vec2-xls-r-300m model, supporting Guarani (gn).

An automatic speech recognition model fine-tuned on the Upper Sorbian (hsb) dataset based on facebook/wav2vec2-xls-r-300m

This model is an automatic speech recognition model fine-tuned on the Romansh-Sursilvan dialect dataset based on facebook/wav2vec2-xls-r-300m, achieving a 24.09% Word Error Rate (WER) on the Common Voice 8 test set.

This is an automatic speech recognition model fine-tuned on the Upper Sorbian (HSB) dataset based on facebook/wav2vec2-xls-r-300m, achieving a word error rate (WER) of 0.4393 on the Common Voice 8 test set.

This model is an automatic speech recognition (ASR) model fine-tuned on the Erzya language (MYV) dataset based on facebook/wav2vec2-xls-r-300m, achieving a 65.15% word error rate (WER) on the Common Voice 8 test set.