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dc.contributor.author | Kenan Ahmed, 01-134201-033 | |
dc.contributor.author | Muhammad Umer, 01-134201-098 | |
dc.date.accessioned | 2024-03-11T06:44:53Z | |
dc.date.available | 2024-03-11T06:44:53Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | http://hdl.handle.net/123456789/17058 | |
dc.description | Supervised by Dr. Muhammad Asfand-e-Yar | en_US |
dc.description.abstract | This research project introduces an innovative Emotion Detection and Content Analysis system aimed at revolutionizing customer support. In the digital age, exceptional customer service is a key differentiator for businesses. This system combines cutting-edge technologies to enhance support quality, ensure user authentication, and gain insights into user interactions. Key components include user authentication, real-time audio processing for emotion detection, content analysis, and robust database management. The project prioritizes performance, reliability, and security, offering real-time analysis and protection measures. By deploying this system, businesses can provide more personalized support and gain deeper insights into customer interactions, ultimately improving the overall customer experience. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Computer Sciences | en_US |
dc.relation.ispartofseries | BS(CS);P-02165 | |
dc.subject | Detection | en_US |
dc.subject | Emotional Intensity | en_US |
dc.subject | Speech and Content Analysis | en_US |
dc.title | Detection of Emotional Intensity from Speech and Content Analysis | en_US |
dc.type | Project Reports | en_US |