Fourier Acoustics Sound Radiation And Nearfield Acoustical Holography

Musicians perform music according to their own interpretations. How does a player realize his/her interpretation of a piece of music in the form of tones? How is his/her intention understood by a listener? The relations among the performers' intentions, intensity of tones produced by the performers, and listeners' perception were investigated quantitatively. The noteworthy findings were as follows. (1) Crescendo was easier to recognize than decrescendo. (2) It appeared that rising pitch enhanced an impression of crescendo, and falling pitch enhanced that of decrescendo. (3) The influence of “impression of the end” on crescendo was suggested. These findings were confirmed in the experiments by means of synthesized sound sequences and under well‐controlled conditions.

The communication of dynamics between musicians and listeners through musical performance

Because humans lack a sensory vocabulary for auditory experiences, timbral qualities of sounds are often conceptualized and communicated through readily available sensory attributes from different modalities (e.g., bright, warm, sweet) but also through the use of onomatopoeic attributes (e.g., ringing, buzzing, shrill) or nonsensory attributes relating to abstract constructs (e.g., rich, complex, harsh). The analysis of the linguistic description of timbre, or timbre semantics, can be considered as one way to study its perceptual representation empirically. In the most commonly adopted approach, timbre is considered as a set of verbally defined perceptual attributes that represent the dimensions of a semantic timbre space. Previous studies have identified three salient semantic dimensions for timbre along with related acoustic properties. Comparisons with similarity-based multidimensional models confirm the strong link between perceiving timbre and talking about it. Still, the cognitive and neural mechanisms of timbre semantics remain largely unknown and underexplored, especially when one looks beyond the case of acoustic musical instruments.

The Semantics of Timbre

It has been argued that the relative position of spectral envelopes along the frequency axis serves as a cue for musical instrument size (e.g., violin vs viola) and that the shape of the spectral envelope encodes family identity (violin vs flute). It is further known that fundamental frequency (F0), F0-register for specific instruments, and dynamic level strongly affect spectral properties of acoustical instrument sounds. However, the associations between these factors have not been rigorously quantified for a representative set of musical instruments. Here, we analyzed 5640 sounds from 50 sustained orchestral instruments sampled across their entire range of F0s at three dynamic levels. Regression of spectral centroid (SC) values that index envelope position indicated that smaller instruments possessed higher SC values for a majority of instrument classes (families), but SC also correlated with F0 and was strongly and consistently affected by the dynamic level. Instrument classification using relatively low-dimensional cepstral audio descriptors allowed for discrimination between instrument classes with accuracies beyond 80%. Envelope shape became much less indicative of instrument class whenever the classification problem involved generalization to different dynamic levels or F0-registers. These analyses confirm that spectral envelopes encode information about instrument size and family identity and highlight their dependence on F0(-register) and dynamic level.

/pdf/spectral-envelope-position-and-shape-in-sustained-musical-4y4c6mjdh6.pdf

Spectral envelope position and shape in sustained musical instrument sounds.

Common acoustic sources, like voices or musical instruments, exhibit strong frequency and directional dependence. When transported through complex environments, their anisotropic radiated field undergoes scattering, diffraction, and occlusion before reaching a directionally-sensitive listener. We present the first wave-based interactive auralization system that encodes and renders a complete reciprocal description of acoustic wave fields in general scenes. Our method renders directional effects at freely moving and rotating sources and listeners and supports any tabulated source directivity function and head-related transfer function. We represent a static scene's global acoustic transfer as an 11-dimensional bidirectional impulse response (BIR) field, which we extract from a set of wave simulations. We parametrically encode the BIR as a pair of radiating and arriving directions for the perceptually-salient initial (direct) response, and a compact 6 × 6 reflections transfer matrix capturing indirect energy transfer with scene-dependent anisotropy. We render our encoded data with an efficient and scalable algorithm - integrated in the Unreal Engine™ - whose CPU performance is agnostic to scene complexity and angular source/listener resolutions. We demonstrate convincing effects that depend on detailed scene geometry, for a variety of environments and source types.

Directional sources and listeners in interactive sound propagation using reciprocal wave field coding

Violin (classical) Violin_historical 430 Hz G3-C7 G3-C7 Normal of the soundboard aiming at Mic#25, Scroll aiming at between Mic#02 and Mic#03 Daniel Deuter 200905-18 14:15 15:15 Instrument: Neil Kristóv Értz (1998, rev. 2003), Copy of Guaneri; Bow: Violin Bow (50 g), René Groppe (Metz, 1997), Copy of baroque model (17th century); Strings: E String: Catgut (Damian Dlugolecki, 0.62 mm); A String: Catgut (Nicholas Baldock, Kathedrale Strings, 0.74 mm); D String: Catgut (+0.25 mm Silver, 1.12mm, Nicholas Baldock, LuxLine); G String: Catgut, Silver, diameter unknown

/pdf/a-database-of-anechoic-microphone-array-measurements-of-aagzz7dl26.pdf

A Database of Anechoic Microphone Array Measurements of Musical Instruments

In a series of measurements, the sound power of 40 musical instruments, including all standard modern orchestral instruments, as well as some of their historic precursors from the classical and the baroque epoch, was determined using the enveloping surface method with a 32-channel spherical microphone array according to ISO 3745 Single notes were recorded at the extremes of the dynamic range (pp and ff) over the entire pitch range In a subsequent audio content analysis, audio features were determined for all 3482 single notes using the timbre toolbox In order to analyze the relative contributions of timbre- and amplitude-related properties to the expression of musical dynamics in different instruments, Bayesian linear discriminant analysis and generalized linear mixed modelling were employed to determine those audio features discriminating best between extremes of dynamics both within and across instruments The results from these measurements and statistical analyses thus deliver a comprehensive picture of the acoustical manifestation of “musical dynamics” with respect to sound power and timbre for all standard orchestral instruments

/pdf/sound-power-and-timbre-as-cues-for-the-dynamic-strength-of-1t0wdar2ex.pdf

Sound power and timbre as cues for the dynamic strength of orchestral instruments.

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A Database of Anechoic Microphone Array Measurements of Musical Instruments

Sound power and timbre as cues for the dynamic strength of orchestral instruments.