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Feature Description
Emotions play a significant role in human communication, and the ability to recognise emotions from audio can greatly enhance various applications, including customer service, mental health monitoring, and interactive voice response systems. This project aims to develop a deep learning-based system for accurately recognising emotions from audio recordings.
Use Case
Customer Service Improvement: Detecting emotions to better respond to customer needs. Mental Health Monitoring: Analysing emotional states for early detection of mental health issues. Social Media Analysis: Monitoring emotional trends and responses in social media posts. Educational Tools: Providing feedback on emotional tone in public speaking or language learning.
Benefits
Enhanced User Experience: Providing more empathetic and responsive interactions. Improved Mental Health Support: Offering better monitoring and support for mental health. Increased Efficiency: Automating emotion detection to improve response times. Valuable Insights: Gaining a deeper understanding of user emotions for better decision-making. Technological Advancement: Pushing the boundaries of deep learning applications in audio processing.
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Priority
High
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