Treatment for Insomnia using Music Genre prediction using Convolutional Recurrent Neural Network
M. Kiruthiga Devi, U Surya, K. Unnamalai, Tharani. R. K · 2022 1st International Conference on Computational Science and Technology (ICCST) · 2022
Chronic health issues like high blood pressure, heart disease, diabetes, kidney disease, obesity, stroke, and depression have been related to sleep deprivation. Healthcare professionals are becoming increasingly aware of the importance of sleep, which affects overall health and wellness as a sign of vitality. The results of research on music therapy and its effectiveness as a strong, economical intervention will be discussed. the capacity of music to promote sleep under conditions of health and sickness. With tailored genres and data, we use transfer learning techniques to train a music genre classification system. The model takes the spectrogram or sonogram of music frames as an input and then assesses the image using a Convolutional Neural Network (CNN) and a Recurrent Neural Network (RNN). The system generates a vector of predicted genres with the highest level of accuracy as its output. This technique will be helpful in analyzing or predicting the character or mood based on musical tastes, which helps alleviate tension, worry, and depression.