@inproceedings{eea9a661ba6f44a0ac7ccc18d24ce757,
title = "Soothing Music Recommendation System for Mothers with Postpartum Depression Using CRNN Method",
abstract = "Postpartum depression is a significant disease but rarely recognized and treated. There are several treatments can be done to reduce the occurrence of depression, one of them are music therapy. Everyone can apply music therapy by choosing the music that suits them. For postpartum depression sufferers, the selection of soothing music is very important, so a music recommendation system is needed to choose soothing music. The purpose of this paper is how to develop a soothing music recommendation system for mothers with postpartum depression or who are at risk of suffering from postpartum depression and whether the method used can provide accurate recommendations. The method used is Convolutional Recurrent Neural Network or CRNN. The results obtained from experiments using CNN and CRNN methods in developing a music recommendation system are quite good results in detecting music tempo for both methods.",
keywords = "CRNN, Music, Music Recommendation System, Postpartum depression, Tempo",
author = "Nabila, {Putri Aliya} and Vinarti, {Retno Aulia} and Edwin Riksakomara and Raras Tyasnurita",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 4th IEEE International Conference of Computer Science and Information Technology, ICOSNIKOM 2022 ; Conference date: 19-10-2022 Through 21-10-2022",
year = "2022",
doi = "10.1109/ICOSNIKOM56551.2022.10034898",
language = "English",
series = "ICOSNIKOM 2022 - 2022 IEEE International Conference of Computer Science and Information Technology: Boundary Free: Preparing Indonesia for Metaverse Society",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ICOSNIKOM 2022 - 2022 IEEE International Conference of Computer Science and Information Technology",
address = "United States",
}