Paper Archive

Bucket brigade devices (BBDs) were invented in the late 1960s as a method of introducing a time-delay into an analog electrical circuit. They work by sampling the input signal at a certain clock rate and shifting it through a chain of capacitors to obtain the delay. BBD chips have been used to build a large variety of analog effects processing devices, ranging from chorus to flanging to echo effects. They have therefore attracted interest in virtual analog modeling and a number of approaches to modeling them digitally have appeared. In this paper, we propose a new model for the bucket-brigade device. This model is based on a variable samplerate, and utilizes the surrounding filtering circuitry found in real devices to avoid the need for the interpolation usually needed in such a variable sample-rate system.

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Noise subspace methods are popular for estimating the parameters of complex sinusoids in the presence of uncorrelated noise and have applications in musical instrument modeling and microphone array processing. One such algorithm, MUSIC (Multiple Signal Classification) has been popular for its ability to resolve closely spaced sinusoids. However, the computational efficiency of MUSIC is relatively low, since it requires an explicit eigenvalue decomposition of an autocorrelation matrix, followed by a linear search over a large space. In this paper, we discuss methods for and the benefits of converting the Toeplitz structure of the autocorrelation matrix to circulant form, so that eigenvalue decomposition can be replaced by a Fast Fourier Transform (FFT) of one row of the matrix. This transformation requires modeling the signal as at least approximately periodic over some duration. For these periodic signals, the pseudospectrum calculation becomes trivial and the accuracy of the frequency estimates only depends on how well periodicity detection works. We derive a closed-form expression for the pseudospectrum, yielding large savings in computation time. We test our algorithm to resolve closely spaced piano partials.

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Wave Digital Filters were developed to discretize linear time invariant lumped systems, particularly electronic circuits. The timeinvariant assumption is baked into the underlying theory and becomes problematic when simulating audio circuits that are by nature time-varying. We present extensions to WDF theory that incorporate proper numerical schemes, allowing for the accurate simulation of time-varying systems. We present generalized continuous-time models of reactive components that encapsulate the time-varying lossless models presented by Fettweis, the circuit-theoretic time-varying models, as well as traditional LTI models as special cases. Models of timevarying reactive components are valuable tools to have when modeling circuits containing variable capacitors or inductors or electrical devices such as condenser microphones. A power metric is derived and the model is discretized using the alpha-transform numerical scheme and parametric wave definition. Case studies of circuits containing time-varying resistance and capacitance are presented and help to validate the proposed generalized continuous-time model and discretization.

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Soundscape research is concerned with the study and understanding of our relationship with our surrounding acoustic environments and the sonic elements that they are comprised of. Whilst much of this research has focussed on sound alone, any practical application of soundscape methodologies should consider the interaction between aural and visual environmental features: an interaction known as cross-modal perception. This presents an avenue for soundscape research exploring how an environment’s visual features can affect an individual’s experience of the soundscape of that same environment. This paper presents the results of two listening tests1 : one a preliminary test making use of static stereo UHJ renderings of first-order-ambisonic (FOA) soundscape recordings and static panoramic images; the other using YouTube as a platform to present dynamic binaural renderings of the same FOA recordings alongside full motion spherical video. The stimuli for these tests were recorded at several locations around the north of England including rural, urban, and suburban environments exhibiting soundscapes comprised of many natural, human, and mechanical sounds. The purpose of these tests was to investigate how the presence of visual stimuli can alter soundscape perception and categorisation. This was done by presenting test subjects with each soundscape alone and then with visual accompaniment, and then comparing collected subjective evaluation data. Results indicate that the presence of certain visual features can alter the emotional state evoked by exposure to a soundscape, for example, where the presence of ‘green infrastructure’ (parks, trees, and foliage) results in a less agitating experience of a soundscape containing high levels of environmental noise. This research represents an important initial step toward the integration of virtual reality technologies into soundscape research, and the use of suitable tools to perform subjective evaluation of audiovisual stimuli. Future research will consider how these methodologies can be implemented in real-world applications.

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