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  • 标题:Frequency-Zooming ARMA Modeling for Analysis of Noisy String Instrument Tones
  • 本地全文:下载
  • 作者:Paulo A. A. Esquef ; Matti Karjalainen ; Vesa Välimäki
  • 期刊名称:EURASIP Journal on Advances in Signal Processing
  • 印刷版ISSN:1687-6172
  • 电子版ISSN:1687-6180
  • 出版年度:2003
  • 卷号:2003
  • 期号:10
  • 页码:953-967
  • DOI:10.1155/S1110865703304020
  • 出版社:Hindawi Publishing Corporation
  • 摘要:

    This paper addresses model-based analysis of string instrument sounds. In particular, it reviews the application of autoregressive (AR) modeling to sound analysis/synthesis purposes. Moreover, a frequency-zooming autoregressive moving average (FZ-ARMA) modeling scheme is described. The performance of the FZ-ARMA method on modeling the modal behavior of isolated groups of resonance frequencies is evaluated for both synthetic and real string instrument tones immersed in background noise. We demonstrate that the FZ-ARMA modeling is a robust tool to estimate the decay time and frequency of partials of noisy tones. Finally, we discuss the use of the method in synthesis of string instrument sounds.

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