國立虎尾科技大學 |

Proceedings of the 6th Conference on Sound and Music Technology (CSMT) = Revised Selected Papers /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Proceedings of the 6th Conference on Sound and Music Technology (CSMT)/ edited by Wei Li, Shengchen Li, Xi Shao, Zijin Li.
其他題名:	Revised Selected Papers /
其他作者:	Li, Wei.
面頁冊數:	VIII, 107 p.online resource. :
Contained By:	Springer Nature eBook
標題:	Mathematics. -
電子資源:	https://doi.org/10.1007/978-981-13-8707-4
ISBN:	9789811387074

Proceedings of the 6th Conference on Sound and Music Technology (CSMT) = Revised Selected Papers /
Proceedings of the 6th Conference on Sound and Music Technology (CSMT)Revised Selected Papers /[electronic resource] :edited by Wei Li, Shengchen Li, Xi Shao, Zijin Li. - 1st ed. 2019. - VIII, 107 p.online resource. - Lecture Notes in Electrical Engineering,5681876-1100 ;. - Lecture Notes in Electrical Engineering,317.

A Novel Singer Identification Using GMM-UBM -- A Practical Singing Voice Detection System Based on GRU-RNN -- Multimodal Music Emotion Recognition Using Unsupervised Deep Neural Networks -- Music Summary Detection with Feature Embedding -- Constructing a Multimedia Chinese Musical Instruments Database -- Bird Sound Detection Based on Binarized Convolutional Neural Networks -- An adaptive consistent Dictionary Learning for audio declipping -- A Comparison of Attention Mechanisms of Convolutional Neural Network in Weakly Labelled Audio Tagging -- A Standard MIDI File Steganography Based on Music Perception.

This book discusses the use of advanced techniques to produce and understand music in a digital way. It gathers the first-ever English-language proceedings of the Conference on Sound and Music Technology (CSMT), which was held in Xiamen, China in 2018. As a leading event, the CSMT reflects the latest advances in acoustic and music technologies in China. Sound and technology are more closely linked than most people assume. For example, signal-processing methods form the basis of music feature extraction, while mathematics provides an objective means of representing current musicological theories and discovering new ones. Moreover, machine-learning methods include popular deep learning algorithms and are used in a broad range of contexts, from discovering patterns in music features to producing music. As these proceedings demonstrate, modern technologies not only offer new ways to create music, but can also help people perceive sound in innovative new ways.

ISBN: 9789811387074

Standard No.: 10.1007/978-981-13-8707-4doiSubjects--Topical Terms:

527692
Mathematics.

LC Class. No.: NX180.M33

Dewey Class. No.: 780.0519

Proceedings of the 6th Conference on Sound and Music Technology (CSMT) = Revised Selected Papers /
LDR:03056nam a22004095i 4500 001 1012562
003 DE-He213
005 20200701122818.0
007 cr nn 008mamaa
008 210106s2019 si | s |||| 0|eng d
020 $a 9789811387074 $9 978-981-13-8707-4
024 7 $a 10.1007/978-981-13-8707-4 $2 doi
035 $a 978-981-13-8707-4
050 4 $a NX180.M33
072 7 $a PBW $2 bicssc
072 7 $a MAT003000 $2 bisacsh
072 7 $a PBW $2 thema
082 0 4 $a 780.0519 $2 23
245 1 0 $a Proceedings of the 6th Conference on Sound and Music Technology (CSMT) $h [electronic resource] : $b Revised Selected Papers / $c edited by Wei Li, Shengchen Li, Xi Shao, Zijin Li.
250 $a 1st ed. 2019.
264 1 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2019.
300 $a VIII, 107 p. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Lecture Notes in Electrical Engineering, $x 1876-1100 ; $v 568
505 0 $a A Novel Singer Identification Using GMM-UBM -- A Practical Singing Voice Detection System Based on GRU-RNN -- Multimodal Music Emotion Recognition Using Unsupervised Deep Neural Networks -- Music Summary Detection with Feature Embedding -- Constructing a Multimedia Chinese Musical Instruments Database -- Bird Sound Detection Based on Binarized Convolutional Neural Networks -- An adaptive consistent Dictionary Learning for audio declipping -- A Comparison of Attention Mechanisms of Convolutional Neural Network in Weakly Labelled Audio Tagging -- A Standard MIDI File Steganography Based on Music Perception.
520 $a This book discusses the use of advanced techniques to produce and understand music in a digital way. It gathers the first-ever English-language proceedings of the Conference on Sound and Music Technology (CSMT), which was held in Xiamen, China in 2018. As a leading event, the CSMT reflects the latest advances in acoustic and music technologies in China. Sound and technology are more closely linked than most people assume. For example, signal-processing methods form the basis of music feature extraction, while mathematics provides an objective means of representing current musicological theories and discovering new ones. Moreover, machine-learning methods include popular deep learning algorithms and are used in a broad range of contexts, from discovering patterns in music features to producing music. As these proceedings demonstrate, modern technologies not only offer new ways to create music, but can also help people perceive sound in innovative new ways.
650 0 $a Mathematics. $3 527692
650 0 $a Signal processing. $3 561459
650 0 $a Image processing. $3 557495
650 0 $a Speech processing systems. $3 564428
650 0 $a Music. $3 649088
650 1 4 $a Mathematics in Music. $3 885668
650 2 4 $a Signal, Image and Speech Processing. $3 670837
700 1 $a Li, Wei. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1024749
700 1 $a Li, Shengchen. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1306814
700 1 $a Shao, Xi. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1306815
700 1 $a Li, Zijin. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1306816
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9789811387067
776 0 8 $i Printed edition: $z 9789811387081
776 0 8 $i Printed edition: $z 9789811387098
830 0 $a Lecture Notes in Electrical Engineering, $x 1876-1100 ; $v 317 $3 1253457
856 4 0 $u https://doi.org/10.1007/978-981-13-8707-4
912 $a ZDB-2-SMA
912 $a ZDB-2-SXMS
950 $a Mathematics and Statistics (SpringerNature-11649)
950 $a Mathematics and Statistics (R0) (SpringerNature-43713)