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rlac-audio-segmenter-chroniques
eglantinefonrose/rlac-audio-segmenter-chroniques
rlac-audio-segmenter-chroniques is a machine learning model from eglantinefonrose. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This is version 0.1 of a Random Forest classifier designed for radio audio segmentation. It identifies specific audio segments (columns, features, or ads) within long radio broadcasts.
Access
Public
Updated Apr 12, 2026
Repo size
2.6 MB
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.pkl2.6 MB · 100%
At a glance
- Access
- Public
- Created
- Apr 12, 2026
- Updated
- Apr 12, 2026
- SHA
- 9ee9c563
Model card
From the Hugging Face model README
RLAC Audio Segmenter - Chroniques
Description
This is version 0.1 of a Random Forest classifier designed for radio audio segmentation. It identifies specific audio segments (columns, features, or ads) within long radio broadcasts.
https://huggingface.co/eglantinefonrose/rlac-audio-segmenter-chroniques
Model Details
- Type: Random Forest Classifier
- Input: 3-second audio segments
- Features: MFCC (13), Spectral Energy (4 bands), Zero-Crossing Rate, RMS, Spectral Centroid, Rolloff, and Bandwidth.
- Version: v0.1
Usage
The model is trained to distinguish between targeted content and background broadcast material. It uses a confidence threshold of 0.89 to minimize false positives during the detection phase.
Author
Maintained by eglantinefonrose.
- Created
- Apr 12, 2026
- Updated
- Apr 12, 2026