wav2vec2-base-10k-voxpopuli-ft-es
| Property | Value |
|---|---|
| License | CC-BY-NC-4.0 |
| Paper | VoxPopuli Paper |
| Author | Facebook AI |
| Target Language | Spanish |
What is wav2vec2-base-10k-voxpopuli-ft-es?
This is a specialized speech recognition model developed by Facebook AI, based on the Wav2Vec2 architecture. It's specifically designed for Spanish language processing, utilizing a base model that was first pretrained on a 10K unlabeled subset of the VoxPopuli corpus and then fine-tuned on Spanish transcribed speech data.
Implementation Details
The model operates on audio input sampled at 16kHz and uses the Wav2Vec2 architecture combined with CTC (Connectionist Temporal Classification) for speech recognition. It leverages the transformer-based architecture to process raw audio waveforms and convert them into text transcriptions.
- Supports batch processing of audio inputs
- Includes built-in audio resampling capabilities
- Optimized for Spanish language speech recognition
- Compatible with the Transformers library
Core Capabilities
- Automatic Speech Recognition (ASR) for Spanish
- Raw audio processing without pre-extraction of features
- Handles variable-length audio inputs
- Production-ready with inference endpoints support
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its specialized training on the VoxPopuli corpus, focusing specifically on Spanish language processing. The combination of pretraining on unlabeled data and fine-tuning on transcribed Spanish speech makes it particularly effective for Spanish ASR tasks.
Q: What are the recommended use cases?
The model is ideal for Spanish speech recognition tasks, particularly in applications requiring transcription of Spanish audio content. It's well-suited for both batch processing and real-time transcription scenarios, with support for inference endpoints.
