# French Speech Recognition

This is a distilled version of Whisper Large V3 specifically optimized for French automatic speech recognition, achieving efficient inference through ctranslate2.

A distilled French version of Whisper-Large-V3, optimized for inference efficiency by reducing decoder layers while maintaining good performance

This is a distilled version of the Whisper-Large-V3 French model, optimized for inference speed and memory usage by reducing the number of decoder layers while maintaining good performance.

Whisper-Large-V3-French-Distilled is a French speech recognition model obtained by reducing the decoder layers from 32 to 16 and conducting distillation training on a large-scale dataset. This model significantly reduces memory usage and inference time while maintaining performance.

A French automatic speech recognition model fine-tuned based on OpenAI Whisper-large-v3, supporting case sensitivity, punctuation, and number prediction

This is a French automatic speech recognition model based on the FastConformer architecture, combining Transducer and CTC decoders for high accuracy and multi-domain adaptability.

A French automatic speech recognition model fine-tuned based on openai/whisper-small, trained on the Common Voice 11.0 French dataset, supporting case sensitivity and punctuation prediction.

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.

This is a French automatic speech recognition (ASR) model fine-tuned on the wav2vec2-FR-7K-large model, trained on over 2,200 hours of French speech data.

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

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.

A large-scale French speech recognition model based on the Wav2Vec 2.0 architecture developed by Facebook, supporting automatic speech-to-text tasks

A speech recognition model based on Facebook's Wav2Vec2 architecture, pretrained on 10K unlabeled French data from the VoxPopuli corpus and fine-tuned on French transcription data.

A large-scale speech recognition model pretrained on the VoxPopuli French corpus, supporting French speech-to-text tasks

A wav2vec2 base model trained on 1K hours of French speech, supporting tasks like speech recognition

This is an automatic speech recognition (ASR) model fine-tuned on the Common Voice 8.0 French dataset based on facebook/wav2vec2-xls-r-300m

Large wav2vec2 model trained on 7.6K hours of French speech, including spontaneous, read, and broadcast speech

A wav2vec2 base model trained on 2.9K hours of French speech, supporting spontaneous, read, and broadcast speech

This is an automatic speech recognition (ASR) model fine-tuned on the Common Voice 8.0 French dataset based on facebook/wav2vec2-xls-r-300m, supporting French speech-to-text tasks.

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

Large wav2vec2 model trained on 7.6K hours of French speech data, including spontaneous, read, and broadcast speech