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Genrevim Music Detection DistilHuBERT
This model is a fine-tuned audio classification model based on DistilHuBERT, specifically designed to distinguish between music and non-music audio.
Downloads 61
Release Time : 7/3/2024
Model Overview
This is a fine-tuned audio classification model primarily used for music detection tasks, capable of accurately identifying whether an audio segment contains music content.
Model Features
Efficient Music Detection
Specially optimized for distinguishing between music and non-music audio segments with high accuracy.
Based on DistilHuBERT
Built on the lightweight DistilHuBERT architecture, reducing computational resource requirements while maintaining performance.
Fine-tuned Parameters
Trained with carefully selected hyperparameters, including a learning rate of 5e-5 and the Adam optimizer.
Model Capabilities
Audio Classification
Music Detection
Audio Content Analysis
Use Cases
Audio Content Management
Music Content Filtering
Automatically identify and classify music content in audio files
Accurately distinguish between music and non-music segments
Media Processing
Automatic Audio Tagging
Automatically add music/non-music tags to audio files
Improve audio library management efficiency
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