# No language model dependency

Hindi automatic speech recognition model based on Wav2Vec2 architecture, developed by AI4Bharat

Japanese speech recognition model fine-tuned from facebook/wav2vec2-large-xlsr-53, supporting 16kHz sampled audio input

This model is an automatic speech recognition system trained on the DVoice Dari dataset, using the wav2vec 2.0 architecture, supporting transcription of Moroccan Arabic dialect.

An English speech recognition model fine-tuned from the facebook/wav2vec2-large-xlsr-53 model, trained on the Common Voice 6.1 dataset

A Hindi automatic speech recognition model fine-tuned on low-resource Indian language datasets based on facebook/wav2vec2-large-xlsr-53

This is a Slovenian automatic speech recognition model fine-tuned from Facebook's wav2vec2-large-xlsr-53 model, trained on the Common Voice dataset with a word error rate of 36.04%.

A Ukrainian automatic speech recognition (ASR) model fine-tuned from facebook/wav2vec2-large-xlsr-53, trained on the Common Voice dataset.

Vietnamese speech recognition model based on Wav2Vec2 architecture, fine-tuned on VSLP dataset, supports 16kHz sampled speech input

A Finnish automatic speech recognition model fine-tuned from facebook/wav2vec2-large-xlsr-53, supporting 16kHz sampled audio input.

This is a Hungarian automatic speech recognition model fine-tuned from the facebook/wav2vec2-large-xlsr-53 model, trained using the Common Voice dataset.

A Basque automatic speech recognition model fine-tuned from facebook/wav2vec2-large-xlsr-53, achieving a 15.34% word error rate (WER) on the Common Voice Basque test set.

This is a Marathi speech recognition model based on the Wav2Vec2 architecture, capable of directly converting speech to text.

An automatic speech recognition model fine-tuned on Greek language based on facebook/wav2vec2-large-xlsr-53

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

Georgian automatic speech recognition model fine-tuned from facebook/wav2vec2-large-xlsr-53, supporting 16kHz sampled audio input

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

A Javanese automatic speech recognition model fine-tuned from facebook/wav2vec2-large-xlsr-53, trained on high-quality Javanese TTS data from OpenSLR.

A Sundanese speech recognition model fine-tuned from facebook/wav2vec2-large-xlsr-53, trained on high-quality TTS data from OpenSLR

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

A Sanskrit speech recognition model based on the Wav2Vec2 architecture, capable of converting Sanskrit speech to text

Finnish speech recognition model fine-tuned based on XLSR-53 large model, supports 16kHz audio input

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

An automatic speech recognition model fine-tuned on Tatar language based on facebook/wav2vec2-large-xlsr-53, supporting 16kHz sampled audio input.

This is a Turkish automatic speech recognition model based on the XLSR Wav2Vec2 architecture, trained on the Common Voice Turkish dataset

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

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

A Japanese speech recognition model fine-tuned based on facebook/wav2vec2-large-xlsr-53, supporting hiragana output

A Turkish speech recognition model fine-tuned on the Common Voice dataset based on Facebook's wav2vec2-large-xlsr-53 model

An Interlingua speech recognition model fine-tuned from Facebook's wav2vec2-large-xlsr-53 model, achieving a 22.08% word error rate on the Common Voice Interlingua dataset.

A Luganda speech recognition model fine-tuned from facebook/wav2vec2-large-xlsr-53, trained on Common Voice dataset with 29.52% word error rate

This is an automatic speech recognition model fine-tuned on the Indonesian common voice dataset based on facebook/wav2vec2-large-xlsr-53, supporting Indonesian speech recognition.

Catalan speech recognition model fine-tuned from facebook/wav2vec2-large-xlsr-53, trained on Common Voice and parliamentary speech datasets

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

A Catalan speech recognition model fine-tuned based on facebook/wav2vec2-large-100k-voxpopuli

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

A Portuguese automatic speech recognition (ASR) model fine-tuned from facebook/wav2vec2-large-xlsr-53, achieving a 17.22% word error rate (WER) on the Common Voice Portuguese dataset

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 for Estonian using the Common Voice dataset, based on facebook/wav2vec2-large-xlsr-53

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

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