Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Media Informatika
Diarsyah, M. Ghazali
Unknown Affiliation
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Implementasi CNN-LSTM untuk Music Captioning Diarsyah, M. Ghazali; Setiawan, Dhanny
Media Informatika Vol 23 No 1 (2024)
Publisher : P3M STMIK LIKMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37595/mediainfo.v23i1.213

Abstract

Music has become an integral part of human life, extending its influence across various industries. For many, music is considered a necessity. With the rise of neural network technology, Music Information Retrieval (MIR) has gained prominence as a multidisciplinary field focused on processing music information and its applications. One popular approach for music captioning is the multimodal encoder-decoder architecture, which utilizes the CNN-LSTM algorithm. In this study, we develop a model that simultaneously learns from audio and text data. We explore different design choices for modality fusion, including early fusion, late fusion, and hybrid fusion, to assess their impact
Co-Authors Setiawan, Dhanny