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Proceedings of the 7th Conference on Sound and Music Technology (CSMT): Revised Selected Papers 2020 ed. [Pehme köide]

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  • Formaat: Paperback / softback, 143 pages, kõrgus x laius: 235x155 mm, kaal: 454 g, 1 Illustrations, black and white; VIII, 143 p. 1 illus., 1 Paperback / softback
  • Sari: Lecture Notes in Electrical Engineering 635
  • Ilmumisaeg: 22-Dec-2020
  • Kirjastus: Springer Verlag, Singapore
  • ISBN-10: 981152758X
  • ISBN-13: 9789811527586
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Proceedings of the 7th Conference on Sound and Music Technology (CSMT): Revised Selected Papers 2020 ed.Suurem pilt
  • Formaat: Paperback / softback, 143 pages, kõrgus x laius: 235x155 mm, kaal: 454 g, 1 Illustrations, black and white; VIII, 143 p. 1 illus., 1 Paperback / softback
  • Sari: Lecture Notes in Electrical Engineering 635
  • Ilmumisaeg: 22-Dec-2020
  • Kirjastus: Springer Verlag, Singapore
  • ISBN-10: 981152758X
  • ISBN-13: 9789811527586
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9789811527586.html
The book presents selected papers that have been accepted at the seventh Conference on Sound and Music Technology (CSMT) in December 2019, held in Harbin, Hei Long Jiang, China. CSMT is a domestic 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. The organisers of CSMT hope the conference can serve as a platform for interdisciplinary research. In this proceeding, the paper included covers a wide range topic from speech, signal processing and music understanding, which demonstrates the target of CSMT merging arts and science research together.
Bandwidth Extension WaveNet for Bone-Conducted Speech Enhancement.- Naturalness evaluation of synthetic speech based on residual learning networks.- Detection of Operation Type and Order for Digital Speech.- Singing Voice Detection Using Multi-Feature Deep Fusion with CNN.- A Multi-task Learning Approach for MelodyExtraction.- A post-processing of onset detection based on veri?cation with neural network.- Transfer learning for music classification and regression tasks using artist tags.