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Audioemodetect V1
A
Audioemodetect V1
Developed by PrachiPatel
A text-based emotion classification model capable of identifying six emotions: anger, disgust, fear, happiness, neutrality, and sadness.
Downloads 19
Release Time : 4/13/2023
Model Overview
This model is used for text sentiment analysis and can classify input text into one of six basic emotions. Suitable for scenarios such as social media monitoring and customer feedback analysis.
Model Features
Multi-emotion classification
Capable of recognizing six different emotional states, covering a wide range of emotional expressions.
Text analysis
Focuses on sentiment analysis of text content, suitable for various text inputs.
Model Capabilities
Text emotion classification
Emotion recognition
Sentiment analysis
Use Cases
Social media analysis
User sentiment monitoring
Analyze the emotional tendencies of users towards brands or products on social media.
Helps businesses understand public sentiment and adjust marketing strategies in a timely manner.
Customer service
Customer feedback analysis
Automatically classify the emotional tendencies in customer feedback.
Quickly identify dissatisfied customers and prioritize handling negative feedback.
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