TY - GEN
T1 - Embedded Asian Singer Gender Identification System Based on Singing Voice
AU - Rahmadan, Syahrul Budi
AU - Prasetio, Barlian Henryranu
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/10/24
Y1 - 2023/10/24
N2 - Music is a work of art in the form of pitched vibrations that allow listeners to enjoy a work of art. In a piece of musical art there is a frequency, rhythm, tone, and most importantly the waves that we can hear. Identifying music using machine learning is a very important thing to do because it can make the music industry grow. Therefore, gender identification of singers is carried out in music, especially Asian music. By using MFCC for identification along with GMM for gender classification, a system is created that can carry out this classification with a low budget so that many people can take advantage of this feature. The Raspberry Pi 3 Model B+ is a low-power computer with a high level of mobility so that a gender identification system for singers' voices in Asian music using feature extraction of mel-frequency cepstral coefficients and gaussian mixture models can be implemented in the Raspberry Pi 3 Model B+.
AB - Music is a work of art in the form of pitched vibrations that allow listeners to enjoy a work of art. In a piece of musical art there is a frequency, rhythm, tone, and most importantly the waves that we can hear. Identifying music using machine learning is a very important thing to do because it can make the music industry grow. Therefore, gender identification of singers is carried out in music, especially Asian music. By using MFCC for identification along with GMM for gender classification, a system is created that can carry out this classification with a low budget so that many people can take advantage of this feature. The Raspberry Pi 3 Model B+ is a low-power computer with a high level of mobility so that a gender identification system for singers' voices in Asian music using feature extraction of mel-frequency cepstral coefficients and gaussian mixture models can be implemented in the Raspberry Pi 3 Model B+.
KW - Embedded System
KW - Gender
KW - GMM
KW - MFCC
KW - Music
KW - Raspberry Pi
KW - Voice
UR - https://www.scopus.com/pages/publications/85182396438
U2 - 10.1145/3626641.3626680
DO - 10.1145/3626641.3626680
M3 - Conference contribution
AN - SCOPUS:85182396438
T3 - ACM International Conference Proceeding Series
SP - 556
EP - 561
BT - SIET 2023 - Proceedings of the 8th International Conference on Sustainable Information Engineering and Technology
PB - Association for Computing Machinery
T2 - 8th International Conference on Sustainable Information Engineering and Technology, SIET 2023
Y2 - 24 October 2023 through 25 October 2023
ER -