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Musical Instrument Detection
A foundational speech recognition model based on the wav2vec 2.0 architecture, pre-trained on 960 hours of English speech data
Downloads 2,109
Release Time : 8/25/2023
Model Overview
This model is a foundational speech recognition model using the wav2vec 2.0 architecture, primarily designed for converting speech to text.
Model Features
End-to-End Speech Recognition
Learns speech representations directly from raw audio without manually designed feature extraction
Self-Supervised Pre-training
Utilizes large amounts of unlabeled speech data for pre-training to enhance model generalization
Efficient Fine-tuning
Can be fine-tuned with small amounts of labeled data to adapt to specific speech recognition tasks
Model Capabilities
English Speech Recognition
Speech Feature Extraction
Speech-to-Text Conversion
Use Cases
Speech Technology
Voice Assistants
Used as the speech recognition component for building voice assistants and dialogue systems
Subtitle Generation
Automatically converts audio/video content into text subtitles
Music Analysis
Instrument Detection
Detects types of instruments in audio (as shown in Kaggle examples)
Accuracy metrics available
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