wav2vec2-large-xlsr-53-faroese-100h

Maintained By
carlosdanielhernandezmena

wav2vec2-large-xlsr-53-faroese-100h

PropertyValue
Licensecc-by-4.0
PaperASR Language Resources for Faroese
WER (Test)7.6%
WER (Dev)5.5%

What is wav2vec2-large-xlsr-53-faroese-100h?

This is a specialized automatic speech recognition (ASR) model designed specifically for the Faroese language. It was developed by fine-tuning the facebook/wav2vec2-large-xlsr-53 model using 100 hours of Faroese speech data from the Ravnur Project. The model represents a significant advancement in Faroese language technology, achieving impressive word error rates of 7.6% on test data.

Implementation Details

The model was fine-tuned at the Language and Voice Lab at Reykjavík University using the Ravnursson Faroese Speech and Transcripts dataset. It implements the wav2vec2 architecture, which has proven highly effective for low-resource languages like Faroese.

  • Base Architecture: wav2vec2-large-xlsr-53
  • Training Data: 100 hours of Faroese audio
  • Sampling Rate: 16kHz
  • Evaluation Metric: Word Error Rate (WER)

Core Capabilities

  • Automatic speech recognition for Faroese language
  • High accuracy with 7.6% WER on test set
  • Support for 16kHz audio input
  • Batch processing capabilities
  • Integration with Hugging Face Transformers library

Frequently Asked Questions

Q: What makes this model unique?

This model is one of the first high-performing ASR models specifically trained for the Faroese language, making it a crucial resource for Faroese language technology development.

Q: What are the recommended use cases?

The model is ideal for Faroese speech transcription tasks, language documentation efforts, and building Faroese language applications requiring speech recognition capabilities.

🍰 Interesting in building your own agents?
PromptLayer provides Huggingface integration tools to manage and monitor prompts with your whole team. Get started here.