wav2vec2-large-xlsr-53-spanish

Maintained By
facebook

wav2vec2-large-xlsr-53-spanish

PropertyValue
DeveloperFacebook
LicenseApache 2.0
Downloads8,566
FrameworkPyTorch

What is wav2vec2-large-xlsr-53-spanish?

wav2vec2-large-xlsr-53-spanish is a state-of-the-art automatic speech recognition (ASR) model specifically fine-tuned for Spanish language processing. Built on Facebook's wav2vec2 architecture, this model demonstrates impressive performance with a 17.6% Word Error Rate (WER) on the Common Voice Spanish test set.

Implementation Details

The model utilizes the wav2vec2 architecture with cross-lingual speech representations (XLSR). It processes audio input at 16kHz sample rate and implements CTC (Connectionist Temporal Classification) for speech recognition tasks. The implementation supports both PyTorch and JAX frameworks.

  • Pre-processes audio input through resampling from 48kHz to 16kHz
  • Implements attention masking for efficient processing
  • Uses batch processing capabilities for improved performance
  • Supports direct integration with the Transformers library

Core Capabilities

  • Spanish speech recognition with high accuracy
  • Batch processing of audio files
  • Character-level transcription with punctuation handling
  • Integration with Common Voice dataset

Frequently Asked Questions

Q: What makes this model unique?

This model stands out for its specialized optimization for Spanish language processing, achieving a competitive 17.6% WER on the Common Voice test set. It benefits from the robust wav2vec2 architecture while being specifically tailored for Spanish speech recognition tasks.

Q: What are the recommended use cases?

The model is ideal for Spanish speech transcription tasks, including subtitling, voice command systems, and automated transcription services. It's particularly well-suited for applications requiring batch processing of Spanish audio content.

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