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jcarbonnell/
tempo_detection

Name: tempo_detection
Availability: InStock

pytorch

custom_tempo_nn

mit

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Audio Feature Extraction Models

This repository contains pre-trained models for audio feature extraction, specifically:

Tempo Detection: Estimates the tempo (BPM) of an audio track.

Model Details

Tempo Model

Model Type: Custom CNN architecture for tempo classification.
Input: Audio segments converted to Mel spectrograms followed by autocorrelation.
Output: Predicts Beats Per Minute (BPM) in a range from [85, 170].

Key Detection Models

Key Class Model: Classifies into 12 relative key classes.
Key Quality Model: Determines if the key is Major or Minor.
Input: Audio segments converted to Mel spectrograms.
Output:
- Key Class: One of 12 key signatures.
- Key Quality: Binary classification (0 for Major, 1 for Minor).

Usage

Prerequisites

Python 3.7+
PyTorch
torchaudio
transformers

Loading Models

To use these models with Hugging Face's transformers library:

python

from transformers import [AutoModelForAudioClassification](https://x.com/i/grok?text=AutoModelForAudioClassification)

# Load Tempo Model
tempo_model = AutoModelForAudioClassification.from_pretrained("your_username/tempo_model")

# Load Key Models
key_class_model = AutoModelForAudioClassification.from_pretrained("your_username/key_class_model")
key_quality_model = AutoModelForAudioClassification.from_pretrained("your_username/key_quality_model")

jcarbonnell/tempo_detection