• DocumentCode
    2793152
  • Title

    Singing information processing based on singing voice modeling

  • Author

    Goto, Masataka ; Saitou, Takeshi ; Nakano, Tomoyasu ; Fujihara, Hiromasa

  • Author_Institution
    Nat. Inst. of Adv. Ind. Sci. & Technol. (AIST), Tsukuba, Japan
  • fYear
    2010
  • fDate
    14-19 March 2010
  • Firstpage
    5506
  • Lastpage
    5509
  • Abstract
    In this paper, we propose a novel area of research referred to as singing information processing. To shape the concept of this area, we first introduce singing understanding systems for synchronizing between vocal melody and corresponding lyrics, identifying the singer name, evaluating singing skills, creating hyperlinks between phrases in the lyrics of songs, and detecting breath sounds. We then introduce music information retrieval systems based on similarity of vocal melody timbre and vocal percussion, and singing synthesis systems. Common signal processing techniques for modeling singing voices that are used in these systems, such as techniques for extracting the vocal melody from polyphonic music recordings and modeling the lyrics by using phoneme HMMs for singing voices, are discussed.
  • Keywords
    acoustic signal processing; hidden Markov models; information retrieval systems; musical acoustics; breath sound detection; hyperlinks; lyrics; music information retrieval; phoneme HMM; polyphonic music recordings; signal processing; singing information processing; singing synthesis; singing voice modeling; vocal melody; vocal melody timbre; vocal percussion; Data mining; Disk recording; Information processing; Instruments; Multiple signal classification; Music information retrieval; Signal processing; Signal synthesis; Speech recognition; Timbre; Music; singing information processing; singing voice modeling; vocal melody;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on
  • Conference_Location
    Dallas, TX
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4244-4295-9
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2010.5495212
  • Filename
    5495212