My Account Log in

1 option

Proceedings of the 11th Conference on Sound and Music Technology : Revised Selected Papers from CSMT 2024 / edited by Kun Qian, Li Zhou, Qinglin Meng, Yongwei Gao.

Springer eBooks EBA - Engineering Collection 2025 Available online

View online
Format:
Book
Author/Creator:
Qian, Kun.
Contributor:
Zhou, Li.
Meng, Qinglin.
Gao, Yongwei.
Series:
Lecture Notes in Electrical Engineering, 1876-1119 ; 1404
Language:
English
Subjects (All):
Speech processing systems.
Signal processing.
Acoustical engineering.
Music--Mathematics.
Music.
Music theory.
Speech and Audio Processing.
Engineering Acoustics.
Mathematics in Music.
Theory of Music.
Local Subjects:
Speech and Audio Processing.
Engineering Acoustics.
Mathematics in Music.
Theory of Music.
Physical Description:
1 online resource (171 pages)
Edition:
1st ed. 2025.
Place of Publication:
Singapore : Springer Nature Singapore : Imprint: Springer, 2025.
Summary:
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). .
Contents:
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.
Notes:
Description based on publisher supplied metadata and other sources.
ISBN:
981-9647-83-5
OCLC:
1530377986

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account