# High-precision WER

This model is a Korean automatic speech recognition model fine-tuned on the zeroth_korean dataset based on facebook/wav2vec2-xls-r-300m, with a word error rate of 0.2433.

An acoustic model fine-tuned specifically for Icelandic automatic speech recognition tasks, trained on 967 hours of Icelandic data

This is a FastConformer hybrid model for Russian automatic speech recognition, combining Transducer and CTC decoders with approximately 115 million parameters.

This is a German automatic speech recognition model based on the FastConformer architecture, employing a hybrid training approach with Transformer and CTC, with a parameter size of approximately 115M.

An acoustic model for Spanish automatic speech recognition, fine-tuned for 5 epochs based on facebook/wav2vec2-large-xlsr-53 using approximately 944 hours of Spanish data.

Vietnamese automatic speech recognition model based on wav2vec2 architecture, pre-trained with 13,000 hours of unlabeled YouTube audio and fine-tuned on 250 hours of labeled data

This is a large Conformer-CTC model for Russian automatic speech recognition, trained on approximately 1,636 hours of Russian speech data with about 120 million parameters.

This is a large Conformer-CTC model for Spanish automatic speech recognition (ASR), trained and released by NVIDIA.

This is a large-scale Conformer-Transducer model for French automatic speech recognition, with approximately 120 million parameters, trained on over 1,500 hours of French speech data.

This is a large French automatic speech recognition (ASR) model based on the Conformer architecture, trained using CTC loss function on over 1,500 hours of French speech data.

This model is an automatic speech recognition model fine-tuned on the GARY109/AI_LIGHT_DANCE - ONSET-STEPMANIA2 dataset based on facebook/wav2vec2-large-xlsr-53

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice dataset, primarily designed for Russian speech recognition tasks.

A speech-to-text (S2T) model for automatic speech recognition (ASR)

A speech-to-text (S2T) model for automatic speech recognition (ASR), based on a sequence-to-sequence transformer architecture

Wav2Vec2 is a self-supervised learning-based speech recognition model, pre-trained and fine-tuned on 960 hours of LibriSpeech audio data, supporting English speech transcription.

A speech recognition model fine-tuned on the Singapore English (li_singlish) dataset based on facebook/wav2vec2-xls-r-300m

This model is an automatic speech recognition model fine-tuned on the ONSET-SINGING dataset based on wav2vec2-large-lv60, focusing on singing voice recognition tasks.

This model is a Danish speech recognition model fine-tuned by Siyam/SKYLy on the common_voice dataset

This is a speech recognition model fine-tuned on Filipino speech datasets based on the wav2vec2-large-xlsr-53-english model, supporting English and Filipino speech-to-text tasks.

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the COMMON_VOICE - LT dataset for Lithuanian speech recognition.

This model is a fine-tuned speech recognition model based on facebook/wav2vec2-xls-r-300m on the common_voice dataset

An automatic speech recognition (ASR) model fine-tuned on Arabic speech datasets based on distilhubert

This is a speech recognition model fine-tuned on the Common Voice Irish dataset based on the facebook/wav2vec2-xls-r-300m model, primarily used for automatic speech recognition tasks in Irish.

Portuguese automatic speech recognition model fine-tuned on the CORAA dataset based on facebook/wav2vec2-xls-r-1b

An automatic speech recognition model fine-tuned on the Odia (OR) Common Voice dataset based on facebook/wav2vec2-xls-r-300m

Urdu speech recognition model based on the wav2vec2-large-xls-r-300m architecture, fine-tuned on the Common Voice dataset

A speech-to-text (S2T) model for automatic speech recognition (ASR), based on a sequence-to-sequence transformer architecture

This is a German automatic speech recognition model based on the XLS-R 1B architecture, fine-tuned on multiple German speech datasets including Common Voice 8.0

An Irish Gaelic automatic speech recognition model fine-tuned on wav2vec2-large-xlsr-53, trained on the Common Voice 7.0 dataset

This is an Italian automatic speech recognition model based on the XLS-R 1B architecture, fine-tuned on multiple Italian datasets

This model is a Swedish automatic speech recognition model fine-tuned on the COMMON_VOICE - SV-SE dataset based on facebook/wav2vec2-large-xlsr-53.

This model is an automatic speech recognition model fine-tuned on the Common Voice 8 Basaa dataset based on facebook/wav2vec2-xls-r-1b.

Turkish automatic speech recognition model based on wav2vec2 architecture, fine-tuned on the Common Voice 7.0 Turkish dataset

This is an automatic speech recognition model fine-tuned on the Common Voice 8.0 Hindi dataset based on the facebook/wav2vec2-xls-r-1b model, supporting Hindi speech-to-text tasks.

Russian speech recognition model fine-tuned based on XLS-R 1B architecture, trained on datasets like Common Voice 8.0

This is an automatic speech recognition model fine-tuned on Galician speech datasets based on facebook/wav2vec2-xls-r-300m.

This model is a Czech automatic speech recognition model fine-tuned on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - cs dataset based on facebook/wav2vec2-xls-r-1b.

This is a Portuguese automatic speech recognition model based on the XLS-R 1B architecture, fine-tuned on multiple Portuguese speech datasets.

An end-to-end sequence-to-sequence transformer model for automatic speech recognition (ASR), trained on the LibriSpeech dataset

This model is a speech recognition model fine-tuned on the DementiaBank dataset based on facebook/wav2vec2-large-960h, primarily used for speech-to-text tasks.