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license: mit
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license: mit
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---
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# Audio Feature Extraction Models
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This repository contains pre-trained models for audio feature extraction, specifically:
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- **Key Detection:** Classifies the musical key of an audio track into relative key classes.
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## Model Details
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### Tempo Model
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- **Model Type:** Custom CNN architecture for tempo classification.
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- **Input:** Audio segments converted to Mel spectrograms followed by autocorrelation.
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- **Output:** Predicts Beats Per Minute (BPM) in a range from [85, 170].
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### Key Detection Models
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- **Key Class Model:** Classifies into 12 relative key classes.
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- **Key Quality Model:** Determines if the key is Major or Minor.
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- **Input:** Audio segments converted to Mel spectrograms.
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- **Output:**
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- Key Class: One of 12 key signatures.
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- Key Quality: Binary classification (0 for Major, 1 for Minor).
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## Usage
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### Prerequisites
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- Python 3.7+
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- PyTorch
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- torchaudio
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- transformers
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### Loading Models
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To use these models with Hugging Face's transformers library:
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```python
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from transformers import [AutoModelForAudioClassification](https://x.com/i/grok?text=AutoModelForAudioClassification)
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# Load Tempo Model
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tempo_model = AutoModelForAudioClassification.from_pretrained("your_username/tempo_model")
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# Load Key Models
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key_class_model = AutoModelForAudioClassification.from_pretrained("your_username/key_class_model")
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key_quality_model = AutoModelForAudioClassification.from_pretrained("your_username/key_quality_model")
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