# Common Voice Fine-tuning

Arabic speech recognition model fine-tuned based on OpenAI Whisper-small

Automatic speech recognition model fine-tuned on the Common Voice 11.0 German dataset based on OpenAI's whisper-medium model

A speech recognition model fine-tuned on the Common Voice 11.0 Chinese dataset based on OpenAI Whisper Tiny model

A speech recognition model fine-tuned on the Turkish Common Voice dataset based on OpenAI Whisper-small

Belarusian text-to-speech model based on Microsoft SpeechT5 architecture, fine-tuned on the Common Voice dataset

A Ukrainian text-to-speech model fine-tuned based on Microsoft's SpeechT5 architecture, trained using the Common Voice dataset

This is a speech recognition model fine-tuned on the Serbian Common Voice 11.0 dataset based on OpenAI Whisper Large-V2, achieving a word error rate of 10.76%.

This is a Hindi automatic speech recognition (ASR) model fine-tuned based on OpenAI Whisper Large V2, trained on the Common Voice 11.0 dataset with a word error rate (WER) of 10.05%.

Hindi speech recognition model fine-tuned based on OpenAI Whisper Large-v2, achieving a word error rate of 11.3% on the Common Voice 11.0 Hindi test set

A French speech recognition model fine-tuned on the common_voice_11_0 dataset based on openai/whisper-medium, achieving a standardized WER of 11.1406, outperforming the original model.

A Swedish automatic speech recognition model fine-tuned from facebook/wav2vec2-large-robust, supporting 16kHz sampling rate audio input.

An automatic speech recognition model fine-tuned using the Common Voice 7.0 French dataset, based on the facebook/wav2vec2-xls-r-300m model

A Japanese automatic speech recognition model fine-tuned using the training set of Common Voice 7.0 (Japanese version), based on the facebook/wav2vec2-large-it-voxpopuli model.

A Japanese automatic speech recognition model fine-tuned based on the microsoft/unispeech-sat-large model, trained using the Common Voice 7.0 Japanese dataset.

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

A Japanese automatic speech recognition model fine-tuned using the Common Voice 7.0 (Japanese) dataset, based on the microsoft/unispeech-large-1500h-cv model

An English speech recognition model fine-tuned based on Microsoft's UniSpeech-SAT-Large model, supporting 16kHz sampled audio input.

This is an automatic speech recognition (ASR) model fine-tuned on the German Common Voice 9.0 dataset, based on Facebook's wav2vec2-large-xlsr-53 model.

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

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

An automatic speech recognition model fine-tuned on the Common Voice 8.0 international language dataset based on facebook/wav2vec2-xls-r-300m

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

An automatic speech recognition model fine-tuned on the Common Voice 8 German dataset based on facebook/wav2vec2-xls-r-1b

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

Based on Facebook's wav2vec2-xls-r-300m model, fine-tuned on the Common Voice German dataset, supporting German speech recognition with preserved text case information.

An English fine-tuned speech recognition model based on facebook/wav2vec2-large, using the Common Voice dataset, supporting 16kHz sampled audio input.

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