wav2vec2-large-xlsr-53-hungarian
| Property | Value |
|---|---|
| License | Apache 2.0 |
| Author | jonatasgrosman |
| Downloads | 126,240 |
| Task | Automatic Speech Recognition |
What is wav2vec2-large-xlsr-53-hungarian?
This is a fine-tuned version of Facebook's wav2vec2-large-xlsr-53 model specifically optimized for Hungarian speech recognition. The model was trained on Common Voice 6.1 and CSS10 datasets, achieving state-of-the-art performance with a Word Error Rate (WER) of 31.40% and Character Error Rate (CER) of 6.20%. It's designed to process audio input sampled at 16kHz.
Implementation Details
The model utilizes the Wav2Vec2 architecture, fine-tuned using GPU resources provided by OVHcloud. It implements a transformer-based approach for speech recognition, specifically adapted for Hungarian language characteristics.
- Built on the XLSR-53 large model architecture
- Optimized for 16kHz audio input
- Implements CTC (Connectionist Temporal Classification) for speech recognition
- Trained on Common Voice and CSS10 datasets
Core Capabilities
- Direct transcription of Hungarian speech to text
- Supports batch processing of audio files
- Compatible with both MP3 and WAV audio formats
- Outperforms other Hungarian ASR models in benchmarks
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its superior performance in Hungarian speech recognition, achieving significantly better WER (31.40%) compared to similar models, making it the current best choice for Hungarian ASR tasks.
Q: What are the recommended use cases?
The model is ideal for Hungarian speech transcription tasks, including audio content processing, subtitling, and voice command systems. It's particularly suitable for applications requiring high accuracy in Hungarian language processing.
