Proceedings of the 11th Conference on Sound and Music Technology

Revised Selected Papers from CSMT 2024

AvKun Qian,Li Zhou

Inbunden, Engelska, 2025

Del 1404 i serien Lecture Notes in Electrical Engineering

2 177 kr

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Beskrivning

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).

Produktinformation

Utgivningsdatum:2025-07-23
Mått:155 x 235 x 13 mm
Vikt:352 g
Format:Inbunden
Språk:Engelska
Serie:Lecture Notes in Electrical Engineering
Antal sidor:109
Förlag:Springer Nature Switzerland AG
ISBN:9789819647828

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Innehållsförteckning

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.