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

Record Type:	Electronic resources : Monograph/item
Title/Author:	Proceedings of the 11th Conference on Sound and Music Technologyedited 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.
Contained By:	Springer Nature eBook
Subject:	Acoustical engineeringHandbooks, manuals, etc.
Online resource:	https://doi.org/10.1007/978-981-96-4783-5
ISBN:	9789819647835$q(electronic bk.)

Proceedings of the 11th Conference on Sound and Music Technologyrevised 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 ;v.132..

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$q(electronic bk.)

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

537022
Acoustical engineering
--Handbooks, manuals, etc.

LC Class. No.: TK7882.S65

Dewey Class. No.: 620.2

Proceedings of the 11th Conference on Sound and Music Technologyrevised selected papers from CSMT 2024 /
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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).
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