TY - GEN
T1 - Comparison of the Use of the DEMUCS Neural Network On Different Platforms for the Separation of Sources Of Musical Origin
AU - Alarcon, Raul Perez
AU - Alvaro, Luis Marcelo Pacheco
AU - Rodriguez, Ciro
AU - Puente, Favio Guevara
AU - Petrlik, Ivan
AU - Pomachagua, Yuri
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - This paper makes a comparison between 3 systems deployed on different platforms (Web, Desktop, Mobile) which implement the DEMUCS neural network, responsible for separating sources of musical origin. The objective of this work is to determine on which platform the neural network can be executed more quickly for the use of the average user and from this to propose an optimal architecture for standard development. For this purpose, we selected 12 songs to be separated in the systems of the 3 platforms mentioned and we measured the time it takes for each system to execute the required separation and thus choose the best platform as a starting point. The results and conclusions of the work support the reason for choosing the platform, from which the development architecture was proposed.
AB - This paper makes a comparison between 3 systems deployed on different platforms (Web, Desktop, Mobile) which implement the DEMUCS neural network, responsible for separating sources of musical origin. The objective of this work is to determine on which platform the neural network can be executed more quickly for the use of the average user and from this to propose an optimal architecture for standard development. For this purpose, we selected 12 songs to be separated in the systems of the 3 platforms mentioned and we measured the time it takes for each system to execute the required separation and thus choose the best platform as a starting point. The results and conclusions of the work support the reason for choosing the platform, from which the development architecture was proposed.
KW - Audio
KW - DEMUCS
KW - Deep Learning
KW - Machine Learning
KW - Neural Network
KW - Upmixing
UR - http://www.scopus.com/inward/record.url?scp=85146848555&partnerID=8YFLogxK
U2 - 10.1109/CICN56167.2022.10008289
DO - 10.1109/CICN56167.2022.10008289
M3 - Conference contribution
AN - SCOPUS:85146848555
T3 - Proceedings - 2022 14th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2022
SP - 185
EP - 188
BT - Proceedings - 2022 14th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2022
Y2 - 4 December 2022 through 6 December 2022
ER -