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Record Nr. |
UNINA9910983389903321 |
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Titolo |
Proceedings of the 10th Conference on Sound and Music Technology : Revised Selected Papers from CMST / / edited by Kun Qian, Xin Wang, Qinglin Meng, Mingzhi Chen |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
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ISBN |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (143 pages) |
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Collana |
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Lecture Notes in Electrical Engineering, , 1876-1119 ; ; 1268 |
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Disciplina |
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Soggetti |
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Speech processing systems |
Signal processing |
Acoustical engineering |
Music - Mathematics |
Music theory |
Speech and Audio Processing |
Engineering Acoustics |
Mathematics in Music |
Theory of Music |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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A Holistic Evaluation of Piano Sound Quality -- A Survey Of Singing Voice Synthesis -- Double-Mix-Net: A Multimodal Music Emotion Recognition Network with Multi-Layer Feature Mixing -- Research on Generalization of U-Net Intermediate Block Design for Music Source Separation -- XBeat: A Hybrid Cnn-Transformer Model for Beat And Downbeat Tracking. |
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Sommario/riassunto |
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The book presents selected papers at the 10th Conference on Sound and Music Technology (CSMT) held in June 2023, China. CSMT is a multidisciplinary conference focusing on audio processing and understanding with bias on music and acoustic signals. The primary aim of the conference is to promote the collaboration between art society and technical society in China. In this book, the paper included |
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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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