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Dec 2008

Volume 124, Issue 6, pp. 3351-EL365

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Structural acoustics model of the violin radiativity profile

George Bissinger

J. Acoust. Soc. Am. Volume 124, Issue 6, pp. 4013-4023 (2008); (11 pages) | Cited 2 times

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Violin radiativity profiles are dominated by the Helmholtz-like A0 cavity mode ( ∼ 280 Hz), first corpus bending modes B1− and B1+ ( ∼ 500 Hz), and BH and bridge-filter peaks ( ∼ 2.4 kHz and ∼ 3.5 kHz, respectively), with falloff above ∼ 4 kHz. The B1 modes—dependent on two low-lying free-plate modes—are proposed to excite A0 via coupling to B1-driven in-phase f-hole volume flows. VIOCADEAS data show that A0 radiativity increases primarily as A0-B1− frequency difference decreases, consistent with Meinel’s 1937 experiment for too-thick/too-thin plate thicknesses, plus sound post removal and violin octet baritone results. The vibration→acoustic energy filter, FRAD, computed from shape-material-independent radiation and total damping, peaks at the critical frequency fcrit, estimated from a free-plate mode by analogy to flat-plate bending. Experimentally, fcrit decreased as this plate mode (and B1+) frequency increased. Simulations show that increasing plate thicknesses lowers fcrit, reduces FRAD, and moves the spectral balance toward lower frequencies. Incorporating string→corpus filters (including bridge versus bridge-island impedances) provides a model for overall violin radiativity. This model—with B1 and A0-B1 couplings, and fcrit (computed from a free-plate mode important to B1) strongly affecting the lowest and highest parts of the radiativity profile—substantiates prior empirical B1—sound quality linkages.
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43.75.De Bowed stringed instruments
43.40.At Experimental and theoretical studies of vibrating systems

Beyond the beat: Modeling metric structure in music and performance

Stefan T. Tomic and Petr Janata

J. Acoust. Soc. Am. Volume 124, Issue 6, pp. 4024-4041 (2008); (18 pages)

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Current models for capturing metric structure of recordings of music are concerned primarily with the task of tempo and beat estimation. Even though these models have the potential for extracting other metric and rhythmic information, this potential has not been realized. In this paper, a model for describing the general metric structure of audio signals and behavioral data is presented. This model employs reson filters, rather than the comb filters used in earlier models. The oscillatory nature of reson filters is investigated, as they may be better suited for extracting multiple metric levels in the onset patterns of acoustic signals. The model is tested with several types of sequences of Dirac impulses as inputs, in order to investigate the model’s sensitivity to timing variations and accent structure. The model’s responses to natural stimuli are illustrated, both for excerpts of recorded music from a large database utilized by tempo-estimation models, and sequences of taps from a bimanual tapping task. Finally, the relationship of the model to several other beat-finding and rhythm models is discussed, and several applications and extensions for the model are suggested.
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43.75.Zz Analysis, synthesis, and processing of musical sounds
43.75.Cd Music perception and cognition
43.75.Xz Automatic music recognition, classification, and information retrieval
43.75.St Musical performance, training, and analysis
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