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Testv4
A 5-class audio classification model fine-tuned on the superb dataset based on the wav2vec pre-trained model
Downloads 27
Release Time : 6/20/2024
Model Overview
This model is a fine-tuned version of the wav2vec pre-trained model on the superb dataset, primarily used for audio classification tasks, achieving an accuracy of 62.09% on the validation set
Model Features
Based on wav2vec Pre-training
Utilizes the powerful speech representation capability of wav2vec for transfer learning
5-class Audio Recognition
Capable of classifying audio data into 5 different categories
Moderate Accuracy
Achieves an accuracy of 62.09% on the validation set
Model Capabilities
Audio Classification
Speech Feature Extraction
Use Cases
Speech Analysis
Speech Emotion Recognition
Identify emotion categories in speech
Accuracy 62.09%
Voice Command Classification
Classify voice commands for processing
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