Thought-to-Text Conversion and Reconstruction of Dream using Morse Code Algorithm, Supervised Learning and Generative-AI
Srijon Mandal · 2024
This paper explores a novel approach to brain signal analysis, leveraging advanced techniques such as Morse code encoding/decoding, thought translation, dream conversion, and emotion detection. The primary goal is to enhance the conversion of brain signals into text and images using multi-modal analysis with OpenAI, offering significant benefits in treating stress disorders, PTSD, ADHD, memory loss, and aiding disabled individuals. We propose a methodology for generating synthetic datasets of brain signals and corresponding texts, utilizing machine learning algorithms to predict these mappings. Random Forest (RF) provides best accuracy. This approach is augmented by integrating emotional and stress metrics from devices like Muse and Flowtime. creating a comprehensive system for braincomputer interfacing.