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.

Original languageEnglish
Title of host publicationICOSNIKOM 2022 - 2022 IEEE International Conference of Computer Science and Information Technology
Subtitle of host publicationBoundary Free: Preparing Indonesia for Metaverse Society
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350399073
DOIs
Publication statusPublished - 2022
Event4th IEEE International Conference of Computer Science and Information Technology, ICOSNIKOM 2022 - Virtual, Online, Indonesia
Duration: 19 Oct 202221 Oct 2022

Publication series

NameICOSNIKOM 2022 - 2022 IEEE International Conference of Computer Science and Information Technology: Boundary Free: Preparing Indonesia for Metaverse Society

Conference

Conference4th IEEE International Conference of Computer Science and Information Technology, ICOSNIKOM 2022
Country/TerritoryIndonesia
CityVirtual, Online
Period19/10/2221/10/22

Keywords

  • CRNN
  • Music
  • Music Recommendation System
  • Postpartum depression
  • Tempo

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