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Ast Finetuned Audioset 10 10 0.4593 Finetuned Gtzan
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Ast Finetuned Audioset 10 10 0.4593 Finetuned Gtzan

Developed by Bhanu9Prakash
This is an audio classification model based on the AST (Audio Spectrogram Transformer) architecture, fine-tuned on the GTZAN music genre classification dataset with an accuracy rate of 92%.
Audio Classification
Transformers
Open Source License:Bsd-3-clause#Music classification#High accuracy#Audio feature extraction
Downloads 50
Release Time : 7/11/2023

Model Overview

This model is specifically designed for music genre classification tasks and can identify 10 different music genres. Based on the AST architecture, it was pre-trained on the AudioSet dataset and then fine-tuned on the GTZAN dataset.

Model Features

High accuracy
Achieves 92% classification accuracy on the GTZAN test set.
Transformer-based architecture
Utilizes the AST (Audio Spectrogram Transformer) architecture for processing audio spectrograms.
Two-stage training
Pre-trained on the large-scale AudioSet dataset and then fine-tuned on the GTZAN dataset.

Model Capabilities

Music genre classification
Audio feature extraction
Audio content analysis

Use Cases

Music services
Automatic music classification
Automatically classify uploaded music files for music streaming platforms.
Accurately identifies 10 music genres.
Music analysis
Music recommendation system
Feature extraction and classification based on music content.
Enhances the content understanding capability of recommendation systems.
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