wav2vec2-large-xlsr-53-french
| Property | Value |
|---|---|
| License | Apache 2.0 |
| Author | jonatasgrosman |
| Base Model | facebook/wav2vec2-large-xlsr-53 |
| Test WER | 17.65% (13.59% with LM) |
What is wav2vec2-large-xlsr-53-french?
This is a specialized French speech recognition model fine-tuned on the Common Voice 6.1 dataset. It's based on Facebook's wav2vec2-large-xlsr-53 architecture and has been optimized for French language audio processing at 16kHz sampling rate. The model demonstrates strong performance with a Word Error Rate (WER) of 17.65%, which improves to 13.59% when combined with a language model.
Implementation Details
The model utilizes the wav2vec2 architecture, specifically tailored for French speech recognition. It's been trained using GPU resources provided by OVHcloud and implements state-of-the-art speech recognition techniques.
- Supports 16kHz audio input processing
- Implements CTC-based speech recognition
- Achieves 4.89% Character Error Rate (CER)
- Compatible with the HuggingSound library for easy implementation
Core Capabilities
- Direct speech-to-text transcription without language model
- Enhanced accuracy with optional language model integration
- Batch processing of audio files
- Robust performance on varied French speech inputs
Frequently Asked Questions
Q: What makes this model unique?
The model combines the powerful XLSR-53 architecture with specific French language optimization, achieving impressive accuracy metrics while maintaining flexibility in implementation. Its ability to function both with and without a language model makes it versatile for different use cases.
Q: What are the recommended use cases?
This model is ideal for French speech transcription tasks, particularly in applications requiring 16kHz audio processing. It's suitable for both academic and production environments, especially when high accuracy in French speech recognition is required.
