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Music Source Separation Using ASPP Based on Coupled U-Net Model

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@article{IJASEIT12833,
   author = {Suwon Yang and Daewon Lee},
   title = {Music Source Separation Using ASPP Based on Coupled U-Net Model},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {11},
   number = {2},
   year = {2021},
   pages = {589--594},
   keywords = {Active noise canceling; sound source separation; music source separation; U-net structure; coupled U-Net structure; Atrous Spatial Pyramid Pooling.},
   abstract = {

Noise has established itself as one of the factors that interfere with modern human life, and various noise canceling techniques have been studied to prevent noise. While the old era's noise-canceling technique focused on the physical soundproofing technique, multiple studies have been conducted on the active noise canceling technique that removes only the activated noise in the current era. Active noise canceling (ANC) or digital noise-canceling technology is based on the sound source separation method. This leads to sound source separation technology, which refers to the technology to separate individual sound signals from mixture sounds. Most of the source separation technologies focus on improving speech, not noise reduction. This technology makes it possible to obtain desired sound information more accurately and further improves noise-canceling technology by eliminating unwanted sound information. To provide deeper capability and more enhanced sound separation than the existing structure, we are focused on coupled U-Net model and Atrous spatial pyramid pooling technique (ASPP). This paper presents the music source separation method that combined Coupled U-Net structure with Atrous spatial pyramid pooling technique. To prove the proposed source separation method, we compared GNSDR, GSIR, and GSAR using MIR-1K, a data set that can evaluate the performance of the music source separation. Performance results show that the proposed source separation method overcame other methods' disadvantages and strengthened the feature map.

},    issn = {2088-5334},    publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},    url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12833},    doi = {10.18517/ijaseit.11.2.12833} }

EndNote

%A Yang, Suwon
%A Lee, Daewon
%D 2021
%T Music Source Separation Using ASPP Based on Coupled U-Net Model
%B 2021
%9 Active noise canceling; sound source separation; music source separation; U-net structure; coupled U-Net structure; Atrous Spatial Pyramid Pooling.
%! Music Source Separation Using ASPP Based on Coupled U-Net Model
%K Active noise canceling; sound source separation; music source separation; U-net structure; coupled U-Net structure; Atrous Spatial Pyramid Pooling.
%X 

Noise has established itself as one of the factors that interfere with modern human life, and various noise canceling techniques have been studied to prevent noise. While the old era's noise-canceling technique focused on the physical soundproofing technique, multiple studies have been conducted on the active noise canceling technique that removes only the activated noise in the current era. Active noise canceling (ANC) or digital noise-canceling technology is based on the sound source separation method. This leads to sound source separation technology, which refers to the technology to separate individual sound signals from mixture sounds. Most of the source separation technologies focus on improving speech, not noise reduction. This technology makes it possible to obtain desired sound information more accurately and further improves noise-canceling technology by eliminating unwanted sound information. To provide deeper capability and more enhanced sound separation than the existing structure, we are focused on coupled U-Net model and Atrous spatial pyramid pooling technique (ASPP). This paper presents the music source separation method that combined Coupled U-Net structure with Atrous spatial pyramid pooling technique. To prove the proposed source separation method, we compared GNSDR, GSIR, and GSAR using MIR-1K, a data set that can evaluate the performance of the music source separation. Performance results show that the proposed source separation method overcame other methods' disadvantages and strengthened the feature map.

%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12833 %R doi:10.18517/ijaseit.11.2.12833 %J International Journal on Advanced Science, Engineering and Information Technology %V 11 %N 2 %@ 2088-5334

IEEE

Suwon Yang and Daewon Lee,"Music Source Separation Using ASPP Based on Coupled U-Net Model," International Journal on Advanced Science, Engineering and Information Technology, vol. 11, no. 2, pp. 589-594, 2021. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.11.2.12833.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Yang, Suwon
AU  - Lee, Daewon
PY  - 2021
TI  - Music Source Separation Using ASPP Based on Coupled U-Net Model
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 11 (2021) No. 2
Y2  - 2021
SP  - 589
EP  - 594
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - Active noise canceling; sound source separation; music source separation; U-net structure; coupled U-Net structure; Atrous Spatial Pyramid Pooling.
N2  - 

Noise has established itself as one of the factors that interfere with modern human life, and various noise canceling techniques have been studied to prevent noise. While the old era's noise-canceling technique focused on the physical soundproofing technique, multiple studies have been conducted on the active noise canceling technique that removes only the activated noise in the current era. Active noise canceling (ANC) or digital noise-canceling technology is based on the sound source separation method. This leads to sound source separation technology, which refers to the technology to separate individual sound signals from mixture sounds. Most of the source separation technologies focus on improving speech, not noise reduction. This technology makes it possible to obtain desired sound information more accurately and further improves noise-canceling technology by eliminating unwanted sound information. To provide deeper capability and more enhanced sound separation than the existing structure, we are focused on coupled U-Net model and Atrous spatial pyramid pooling technique (ASPP). This paper presents the music source separation method that combined Coupled U-Net structure with Atrous spatial pyramid pooling technique. To prove the proposed source separation method, we compared GNSDR, GSIR, and GSAR using MIR-1K, a data set that can evaluate the performance of the music source separation. Performance results show that the proposed source separation method overcame other methods' disadvantages and strengthened the feature map.

UR - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12833 DO - 10.18517/ijaseit.11.2.12833

RefWorks

RT Journal Article
ID 12833
A1 Yang, Suwon
A1 Lee, Daewon
T1 Music Source Separation Using ASPP Based on Coupled U-Net Model
JF International Journal on Advanced Science, Engineering and Information Technology
VO 11
IS 2
YR 2021
SP 589
OP 594
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 Active noise canceling; sound source separation; music source separation; U-net structure; coupled U-Net structure; Atrous Spatial Pyramid Pooling.
AB 

Noise has established itself as one of the factors that interfere with modern human life, and various noise canceling techniques have been studied to prevent noise. While the old era's noise-canceling technique focused on the physical soundproofing technique, multiple studies have been conducted on the active noise canceling technique that removes only the activated noise in the current era. Active noise canceling (ANC) or digital noise-canceling technology is based on the sound source separation method. This leads to sound source separation technology, which refers to the technology to separate individual sound signals from mixture sounds. Most of the source separation technologies focus on improving speech, not noise reduction. This technology makes it possible to obtain desired sound information more accurately and further improves noise-canceling technology by eliminating unwanted sound information. To provide deeper capability and more enhanced sound separation than the existing structure, we are focused on coupled U-Net model and Atrous spatial pyramid pooling technique (ASPP). This paper presents the music source separation method that combined Coupled U-Net structure with Atrous spatial pyramid pooling technique. To prove the proposed source separation method, we compared GNSDR, GSIR, and GSAR using MIR-1K, a data set that can evaluate the performance of the music source separation. Performance results show that the proposed source separation method overcame other methods' disadvantages and strengthened the feature map.

LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12833 DO - 10.18517/ijaseit.11.2.12833