Download A Feedback Canceling Reverberator A real-time auralization system is described in which room sounds are reverberated and presented over loudspeakers. Room microphones are used to capture room sound sources, with their outputs processed in a canceler to remove the synthetic reverberation also present in the room. Doing so suppresses feedback and gives precise control over the auralization. It also allows freedom of movement and creates a more dynamic acoustic environment for performers or participants in music, theater, gaming, and virtual reality applications. Canceler design methods are discussed, including techniques for handling varying loudspeaker-microphone transfer functions such as would be present in the context of a performance or installation. Tests in a listening room and recital hall show in excess of 20 dB of feedback suppression.
Download Group Delay-Based Allpass Filters for Abstract Sound Synthesis and Audio Effects Processing An algorithm for artistic spectral audio processing and synthesis using allpass filters is presented. These filters express group delay trajectories, allowing fine control of their frequency-dependent arrival times. We present methods for designing the group delay trajectories to yield a novel class of filters for sound synthesis and audio effects processing. A number of categories of group delay trajectory design are discussed, including stair-stepped, modulated, and probabilistic. Synthesis and processing examples are provided.
Download Resizing Rooms in Convolution, Delay Network, and Modal Reverberators In music recording and virtual reality applications, it is often desirable to control the perceived size of a synthesized acoustic space. Here, we demonstrate a physically informed method for enlarging and shrinking room size. A room size parameter is introduced to modify the time and frequency components of convolution, delay network, and modal artificial reverberation architectures to affect the listener’s sense of the size of the acoustic space taking into account air and materials absorption.
Download Contact Sensor Processing for Acoustic Instrument Sensor Matching Using a Modal Architecture This paper proposes a method to filter the output of instrument contact sensors to approximate the response of a well placed microphone. A modal approach is proposed in which mode frequencies and damping ratios are fit to the frequency response of the contact sensor, and the mode gains are then determined for both the contact sensor and the microphone. The mode frequencies and damping ratios are presumed to be associated with the resonances of the instrument. Accordingly, the corresponding contact sensor and microphone mode gains will account for the instrument radiation. The ratios between the contact sensor and microphone gains are then used to create a parallel bank of second-order biquad filters to filter the contact sensor signal to estimate the microphone signal.
Download FAST MUSIC – An Efficient Implementation Of The Music Algorithm For Frequency Estimation Of Approximately Periodic Signals 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.