My implementation of the research paper - All-in-One: Emotion, Sentiment and Intensity Prediction using a Multi-task Ensemble Framework
CS4472 - Mobile Computing Project. Personal Health Companion App designed to help you achieve a balanced lifestyle.
Analyzing the Drugs Descriptions, conditions, reviews and then recommending the medicines for each Health Condition of a Patient.
Aldous is a zero-shot semantic telemetry engine that measures emotional valence purely through geometry. Bypassing generative AI, it evaluates text against multivariate Gaussian concepts in constant O(1) time. Features Latent Concept Erasure for transparent, mathematically verifiable safety guardrails.
"Edith" is a HackHarvard-born AI project enhancing personal wellness by analyzing emotional states through data from wearables like Apple Watches and Fitbits. It's designed to improve user experience and well-being through advanced AI-driven emotion analysis.
A Dashboard demonstrating Sentimental and Emotional analysis of top rated restaurants reviews located in NCR.
2023년 국립국어원 인공 지능 언어 능력 평가: 감정 분석 과제
StimuliXpert improves the synchronization between EEG signals and emotional stimulus and helps the user to report the emotional arousal & valence in real time
AI-powered Islamic emotional support platform that analyzes Arabic text to provide contextually relevant Quranic verses, authentic duas, and personalized guidance. Built with React, Node.js, Firebase, and OpenAI GPT-4o-mini.
Capstone: Implementation of EEG-based user-friendly music composition algorithm
Edison AT is AI emotional depression program. Developed using Python.
This repository is meant to be an inspiration and rapid-start workspace for building apps quickly. It combines experiments, starter flows, and reusable tooling in one growing repo so ideas can move into working prototypes with minimal setup.
Multi-dimensional evaluation of AI responses using semantic alignment, conversational flow, and engagement metrics.
参考文献《Convolutional_Neural_Networks_for_Sentence_Classification》实现对贝因美评论的分析
End-to-end analysis of narrative emotions using NLP, transforming text into a structured dataset and interactive dashboard.
This project utilizes machine learning and deep learning techniques to perform sentiment analysis on text reviews, automatically categorizing them as positive or negative. It provides valuable insights into user opinions and emotions expressed in textual data.
AI content authenticity platform. 10 tools, 17+ metrics. RoBERTa + DistilGPT-2 detection, GEO/SEO analysis, toxicity scoring, emotional analysis, ensemble scoring. React/TypeScript + Python/PyTorch.
An open source visual analysis tool based on FER
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