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Wav2vec2 Base Music Speech Both Classification

Developed by FerhatDk
An audio classification model fine-tuned based on facebook/wav2vec2-base for distinguishing between music and speech
Downloads 20
Release Time : 7/10/2023

Model Overview

This model is a fine-tuned audio classifier based on the wav2vec2-base architecture, specifically designed to differentiate between music and speech audio content. It achieved 98.47% accuracy on the evaluation set.

Model Features

High Accuracy
Achieved 98.47% classification accuracy on the evaluation set
Based on wav2vec2 Architecture
Utilizes the wav2vec2-base pre-trained model for fine-tuning, with excellent audio feature extraction capabilities
Lightweight Training
Requires only 8 training epochs to achieve high performance

Model Capabilities

Audio Classification
Music Recognition
Speech Recognition

Use Cases

Audio Content Analysis
Automatic Music/Speech Classification
Automatically identifies whether audio content is music or speech
98.47% accuracy
Media Management
Automatic Audio Library Classification
Automatically adds music/speech tags to content in audio libraries
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