Emotion Analysis
UNICE intends to innovatively combine various AI and machine-learning technologies—such as voice and facial emotion recognition, blockchain- and NFT-based data security and personalization, and extensibility via openAPI—to analyze and manage users’ emotional states in real time. This will allow us to deliver personalized emotional management services.
Voice Emotion Analysis UNICE will analyze voice data to infer emotional states using an LSTM-based RNN model. By learning and interpreting continuous speech patterns, we will classify emotions extracted from user speech. We plan to use features such as MFCCs, Chroma, and Spectral Contrast to enhance accuracy.
Facial Emotion Recognition UNICE will employ CNN-based deep-learning models, along with tools such as OpenCV and TensorFlow, to recognize users’ faces and classify their emotional expressions. By identifying various facial landmarks, we expect to categorize a range of emotional states accurately.
Integrated Results By combining results from voice and facial analyses, UNICE will gather complementary data. If necessary, we may assign heavier weighting to either voice or facial-emotion analysis to maximize accuracy.
Data Security & Personalization We will use blockchain and NFT technologies to store user-generated or user-provided data securely and establish clear ownership. Users will have control over their data, enhancing both security and privacy.
OpenAPI UNICE will provide an openAPI to enable integration with various services and platforms, giving developers and enterprises the opportunity to utilize our emotion-analysis tools in diverse ways.
By merging these technologies, UNICE aims to analyze users’ emotional states in real time and deliver the appropriate support and services tailored to their individual needs.
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