LEADER 03569nam 22005655 450 001 9910350245703321 005 20251107173101.0 010 $a981-13-8707-9 024 7 $a10.1007/978-981-13-8707-4 035 $a(CKB)4100000008876924 035 $a(DE-He213)978-981-13-8707-4 035 $a(MiAaPQ)EBC5811848 035 $a(PPN)23848632X 035 $a(EXLCZ)994100000008876924 100 $a20190702d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aProceedings of the 6th Conference on Sound and Music Technology (CSMT) $eRevised Selected Papers /$fedited by Wei Li, Shengchen Li, Xi Shao, Zijin Li 205 $a1st ed. 2019. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2019. 215 $a1 online resource (VIII, 107 p.) 225 1 $aLecture Notes in Electrical Engineering,$x1876-1119 ;$v568 311 08$a981-13-8706-0 327 $aA Novel Singer Identification Using GMM-UBM -- A Practical Singing Voice Detection System Based on GRU-RNN -- Multimodal Music Emotion Recognition Using Unsupervised Deep Neural Networks -- Music Summary Detection with Feature Embedding -- Constructing a Multimedia Chinese Musical Instruments Database -- Bird Sound Detection Based on Binarized Convolutional Neural Networks -- An adaptive consistent Dictionary Learning for audio declipping -- A Comparison of Attention Mechanisms of Convolutional Neural Network in Weakly Labelled Audio Tagging -- A Standard MIDI File Steganography Based on Music Perception. 330 $aThis book discusses the use of advanced techniques to produce and understand music in a digital way. It gathers the first-ever English-language proceedings of the Conference on Sound and Music Technology (CSMT), which was held in Xiamen, China in 2018. As a leading event, the CSMT reflects the latest advances in acoustic and music technologies in China. Sound and technology are more closely linked than most people assume. For example, signal-processing methods form the basis of music feature extraction, while mathematics provides an objective means of representing current musicological theories and discovering new ones. Moreover, machine-learning methods include popular deep learning algorithms and are used in a broad range of contexts, from discovering patterns in music features to producing music. As these proceedings demonstrate, modern technologies not only offer new ways to create music, but can also help people perceive sound in innovative new ways. 410 0$aLecture Notes in Electrical Engineering,$x1876-1119 ;$v568 606 $aMusic$xMathematics 606 $aSignal processing 606 $aMusic 606 $aMathematics in Music 606 $aSignal, Speech and Image Processing 606 $aMusic 615 0$aMusic$xMathematics. 615 0$aSignal processing. 615 0$aMusic. 615 14$aMathematics in Music. 615 24$aSignal, Speech and Image Processing. 615 24$aMusic. 676 $a780.0519 702 $aLi$b Wei$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLi$b Shengchen$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aShao$b Xi$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLi$b Zijin$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910350245703321 996 $aProceedings of the 6th Conference on Sound and Music Technology (CSMT)$92508224 997 $aUNINA