東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Linked to FindBook

Google Book

Amazon

博客來

Proceedings of the 11th Conference on Sound and Music Technology = revised selected papers from CSMT 2024 /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Proceedings of the 11th Conference on Sound and Music Technology/ edited by Kun Qian ... [et al.].
Reminder of title:	revised selected papers from CSMT 2024 /
remainder title:	CSMT 2024
other author:	Qian, Kun.
Published:	Singapore :Springer Nature Singapore : : 2025.,
Description:	vii, 109 p. :ill., digital ;24 cm.
[NT 15003449]:	1. Meta-Learning for Domain Generalization in Anomalous Sound Detection -- 2. Online Joint Beat and Downbeat Tracking with Time Series Forecasting Model -- 3. Advancing Metadata-Convolutional Neural Networks with Multi-Supervised Contrastive Learning and Metadata Insights for Respiratory Sound Analysis -- 4. Automatic Performative Transcription of Guitar Music Based on Multimodal Network -- 5. A Framework for the Digital Representation and Rendering of Chinese Jianpu Notation for Constructing a Synthetic OMR Dataset -- 6. Accent Recognition with Auxiliary Task and Contrastive Learning -- 7. Effective Denoising in Music-Present Pubs with Efficient Channel Attention -- 7. Semi-Supervised Self-Learning Enhanced Music Emotion Recognition.
Contained By:	Springer Nature eBook
Subject:	Acoustical engineering - Congresses. -
Online resource:	https://doi.org/10.1007/978-981-96-4783-5
ISBN:	9789819647835

Proceedings of the 11th Conference on Sound and Music Technology = revised selected papers from CSMT 2024 /
Proceedings of the 11th Conference on Sound and Music Technologyrevised selected papers from CSMT 2024 /[electronic resource] :CSMT 2024edited by Kun Qian ... [et al.]. - Singapore :Springer Nature Singapore :2025. - vii, 109 p. :ill., digital ;24 cm. - Lecture notes in electrical engineering,v. 14041876-1119 ;. - Lecture notes in electrical engineering ;volume 1404..

1. Meta-Learning for Domain Generalization in Anomalous Sound Detection -- 2. Online Joint Beat and Downbeat Tracking with Time Series Forecasting Model -- 3. Advancing Metadata-Convolutional Neural Networks with Multi-Supervised Contrastive Learning and Metadata Insights for Respiratory Sound Analysis -- 4. Automatic Performative Transcription of Guitar Music Based on Multimodal Network -- 5. A Framework for the Digital Representation and Rendering of Chinese Jianpu Notation for Constructing a Synthetic OMR Dataset -- 6. Accent Recognition with Auxiliary Task and Contrastive Learning -- 7. Effective Denoising in Music-Present Pubs with Efficient Channel Attention -- 7. Semi-Supervised Self-Learning Enhanced Music Emotion Recognition.

This book presents selected papers at the 11th Conference on Sound and Music Technology (CSMT) held in October 2024, Wuhan, China. CSMT is a multidisciplinary conference focusing on audio processing and understanding with bias on music and acoustic signals. The primary aim of the book is to promote the collaboration between art society and technical society in China. In this book, the paper included covers a wide range topic from speech, signal processing, music understanding, machine learning, and signal processing for advanced medical diagnosis and treatment applications, which demonstrates the target of CSMT merging arts and science research together. Its content caters to scholars, researchers, engineers, artists, and education practitioners not only from academia but also industry, who are interested in audio/acoustics analysis signal processing, music, sound, and artificial intelligence (AI).

ISBN: 9789819647835

Standard No.: 10.1007/978-981-96-4783-5doiSubjects--Topical Terms:

3217004
Acoustical engineering
--Congresses.

LC Class. No.: TK7882.S65

Dewey Class. No.: 620.2

Proceedings of the 11th Conference on Sound and Music Technology = revised selected papers from CSMT 2024 /
LDR:02847nmm a2200373 a 4500 001 2413892
003 DE-He213
005 20250722130252.0
006 m d
007 cr nn 008maaau
008 260205s2025 si s 0 eng d
020 $a 9789819647835 $q (electronic bk.)
020 $a 9789819647828 $q (paper)
024 7 $a 10.1007/978-981-96-4783-5 $2 doi
035 $a 978-981-96-4783-5
040 $a GP $c GP
041 0 $a eng
050 4 $a TK7882.S65
072 7 $a TJF $2 bicssc
072 7 $a UYU $2 bicssc
072 7 $a COM073000 $2 bisacsh
072 7 $a TJF $2 thema
072 7 $a UYU $2 thema
082 0 4 $a 620.2 $2 23
090 $a TK7882.S65 $b P963 2025
245 0 0 $a Proceedings of the 11th Conference on Sound and Music Technology $h [electronic resource] : $b revised selected papers from CSMT 2024 / $c edited by Kun Qian ... [et al.].
246 3 $a CSMT 2024
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2025.
300 $a vii, 109 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in electrical engineering, $x 1876-1119 ; $v v. 1404
505 0 $a 1. Meta-Learning for Domain Generalization in Anomalous Sound Detection -- 2. Online Joint Beat and Downbeat Tracking with Time Series Forecasting Model -- 3. Advancing Metadata-Convolutional Neural Networks with Multi-Supervised Contrastive Learning and Metadata Insights for Respiratory Sound Analysis -- 4. Automatic Performative Transcription of Guitar Music Based on Multimodal Network -- 5. A Framework for the Digital Representation and Rendering of Chinese Jianpu Notation for Constructing a Synthetic OMR Dataset -- 6. Accent Recognition with Auxiliary Task and Contrastive Learning -- 7. Effective Denoising in Music-Present Pubs with Efficient Channel Attention -- 7. Semi-Supervised Self-Learning Enhanced Music Emotion Recognition.
520 $a This book presents selected papers at the 11th Conference on Sound and Music Technology (CSMT) held in October 2024, Wuhan, China. CSMT is a multidisciplinary conference focusing on audio processing and understanding with bias on music and acoustic signals. The primary aim of the book is to promote the collaboration between art society and technical society in China. In this book, the paper included covers a wide range topic from speech, signal processing, music understanding, machine learning, and signal processing for advanced medical diagnosis and treatment applications, which demonstrates the target of CSMT merging arts and science research together. Its content caters to scholars, researchers, engineers, artists, and education practitioners not only from academia but also industry, who are interested in audio/acoustics analysis signal processing, music, sound, and artificial intelligence (AI).
650 0 $a Acoustical engineering $v Congresses. $3 3217004
650 0 $a Music $x Acoustics and physics $v Congresses. $3 3625980
650 0 $a Sound $v Congresses. $3 627467
650 1 4 $a Speech and Audio Processing. $3 3538490
650 2 4 $a Engineering Acoustics. $3 1533220
650 2 4 $a Mathematics in Music. $3 1619562
650 2 4 $a Theory of Music. $3 3603280
700 1 $a Qian, Kun. $3 3288965
710 2 $a SpringerLink (Online service) $3 836513
711 2 $a Conference on Sound and Music Technology $n (11th : $d 2024 : $c Wuhan, China) $3 3790233
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in electrical engineering ; $v volume 1404. $3 3790232
856 4 0 $u https://doi.org/10.1007/978-981-96-4783-5
950 $a Engineering (SpringerNature-11647)