wav2vec2-large-xlsr-53-romanian
| Property | Value |
|---|---|
| License | Apache 2.0 |
| Author | anton-l |
| Test WER | 24.84% |
| Downloads | 32,160 |
What is wav2vec2-large-xlsr-53-romanian?
This is a fine-tuned version of Facebook's wav2vec2-large-xlsr-53 model specifically optimized for Romanian speech recognition. Built on the Common Voice dataset, it represents a significant advancement in Romanian language processing, offering robust automatic speech recognition capabilities with a Word Error Rate (WER) of 24.84% on test data.
Implementation Details
The model is built upon the wav2vec2 architecture and requires input audio to be sampled at 16kHz. It utilizes CTC (Connectionist Temporal Classification) for speech recognition and can be implemented directly without a language model.
- Built on wav2vec2-large-xlsr-53 architecture
- Trained on Common Voice Romanian dataset
- Supports 16kHz audio input
- Implements PyTorch backend
- Features automatic speech preprocessing
Core Capabilities
- Direct speech-to-text transcription for Romanian
- Batch processing support
- Automatic audio resampling
- Attention mask handling
- Real-time inference support
Frequently Asked Questions
Q: What makes this model unique?
This model is specifically optimized for Romanian language processing, offering state-of-the-art speech recognition capabilities with a reasonable WER of 24.84%. It's built on the robust wav2vec2 architecture while being fine-tuned for Romanian-specific phonetics and language patterns.
Q: What are the recommended use cases?
The model is ideal for Romanian speech transcription tasks, including automated subtitling, voice command systems, and speech analysis applications. It's particularly suitable for applications requiring 16kHz audio processing and real-time transcription capabilities.
