03864nam 22006855 450 991101596280332120250722130252.0981-9647-83-510.1007/978-981-96-4783-5(CKB)39697974400041(MiAaPQ)EBC32231033(Au-PeEL)EBL32231033(DE-He213)978-981-96-4783-5(OCoLC)1530377986(EXLCZ)993969797440004120250722d2025 u| 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierProceedings of the 11th Conference on Sound and Music Technology Revised Selected Papers from CSMT 2024 /edited by Kun Qian, Li Zhou, Qinglin Meng, Yongwei Gao1st ed. 2025.Singapore :Springer Nature Singapore :Imprint: Springer,2025.1 online resource (171 pages)Lecture Notes in Electrical Engineering,1876-1119 ;1404981-9647-82-7 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). .Lecture Notes in Electrical Engineering,1876-1119 ;1404Speech processing systemsSignal processingAcoustical engineeringMusicMathematicsMusic theorySpeech and Audio ProcessingEngineering AcousticsMathematics in MusicTheory of MusicSpeech processing systems.Signal processing.Acoustical engineering.MusicMathematics.Music theory.Speech and Audio Processing.Engineering Acoustics.Mathematics in Music.Theory of Music.621.382Qian Kun1688887Zhou Li1834938Meng Qinglin1834939Gao Yongwei1743464MiAaPQMiAaPQMiAaPQBOOK9911015962803321Proceedings of the 11th Conference on Sound and Music Technology4410632UNINA