Technologies are disclosed for improving the efficiency of real-time audio processing, and specifically for improving the efficiency of continuously modifying a real-time audio signal. Efficiency is improved by reducing memory bandwidth requirements and by reducing the amount of processing used to modify the real-time audio signal. In some configurations, memory bandwidth requirements are reduced by selectively transferring active samples in the frequency domain—e.g. avoiding the transfer samples with amplitudes of zero or near-zero. This has particular importance when the specialized hardware retrieves samples from main memory in real-time. In some configurations, the amount of processing needed to modify the audio signal is reduced by omitting operations that do not meaningfully affect the output audio signal. For example, a multiplication of samples may be avoided when at least one of the samples has an amplitude of zero or near-zero.

Technologies are disclosed for improving the efficiency of real-time audio processing, and specifically for improving the efficiency of continuously modifying a real-time audio signal. Efficiency is improved by reducing memory bandwidth requirements and by reducing the amount of processing used to modify the real-time audio signal. In some configurations, memory bandwidth requirements are reduced by selectively transferring active samples in the frequency domain—e.g. avoiding the transfer samples with amplitudes of zero or near-zero. This has particular importance when the specialized hardware retrieves samples from main memory in real-time. In some configurations, the amount of processing needed to modify the audio signal is reduced by omitting operations that do not meaningfully affect the output audio signal. For example, a multiplication of samples may be avoided when at least one of the samples has an amplitude of zero or near-zero.

The implementation of modal processors, which involve the parallel combination resonant filters, may be costly for applications such as artificial reverberation that can require thousands of modes. In one embodiment, the input signal is decomposed into a plurality of subbands, the outputs of which are downsampled. In each downsampled band, resonant filters are applied at the downsampled sampling rate, and their output is upsampled and filtered to form the band output. In these and other embodiments, a feature of responses of the mode filters have been optimized to minimize an aspect of a residual error after a point in time.

Systems and methods for creating a digital audio filter, such as an impulse response filter, using a pickup audio signal provided to an instrument signal capture device and a microphone signal provided to a mobile device are disclosed. In one embodiment, a method includes capturing a first audio signal using a signal capture device, performing frequency analysis on the digitized first audio signal to generate a frequency response spectrum representation, transmitting the frequency response spectrum representation of the first audio signal from the signal capture device to a mobile device, capturing a second audio signal using a microphone on the mobile device, performing frequency analysis on the at least one digitized second audio signal using the mobile device to generate a frequency response spectrum representation, and generating a digital audio filter from the frequency response spectrum representations of the first audio signal and the second audio signal.

The implementation of modal processors, which involve the parallel combination resonant filters, may be costly for applications such as artificial reverberation that can require thousands of modes. In one embodiment, the input signal is decomposed into a plurality of subbands, the outputs of which are downsampled. In each downsampled band, resonant filters are applied at the downsampled sampling rate, and their output is upsampled and filtered to form the band output. In these and other embodiments, a feature of responses of the mode filters have been optimized to minimize an aspect of a residual error after a point in time.

The present invention relates to a method and an apparatus for binaural rendering an audio signal using variable order filtering in frequency domain. To this end, provided are a method for processing an audio signal including: receiving an input audio signal; receiving a set of truncated subband filter coefficients for filtering each subband signal of the input audio signal, the set of truncated subband filter coefficients being constituted by one or more FFT filter coefficients generated by performing FFT by a predetermined block size; generating at least one subframe for each subband; generating at least one filtered subframe for each subband; performing inverse FFT on the filtered subframe for each subband; and generating a filtered subband signal by overlap-adding the transformed subframe for each subband and an apparatus for processing an audio signal using the same.

The present invention relates to a method and an apparatus for binaural rendering an audio signal using variable order filtering in frequency domain. To this end, provided are a method for processing an audio signal including: receiving an input audio signal; receiving a set of truncated subband filter coefficients for filtering each subband signal of the input audio signal, the set of truncated subband filter coefficients being constituted by one or more FFT filter coefficients generated by performing FFT by a predetermined block size; generating at least one subframe for each subband; generating at least one filtered subframe for each subband; performing inverse FFT on the filtered subframe for each subband; and generating a filtered subband signal by overlap-adding the transformed subframe for each subband and an apparatus for processing an audio signal using the same.

The method for adapting a sound converter to a reference sound converter includes the sound converter having a first linear transfer function with a first frequency response, a second linear transfer function with a second frequency response, and a trivial nonlinearity. The sound converter has a non-linear transfer function corresponding to the frequency response from combination of the first linear transfer function, the trivial nonlinearity, and the second linear transfer function. A first frequency spectrum of the reference sound converter is determined at a low input level. A second frequency spectrum of the reference sound converter is determined at a high input level. The second determined frequency spectrum is used as the second frequency response in the second linear transfer function, and the division of the first frequency spectrum by the second frequency spectrum is used as the first frequency response in the first linear transfer function.

The implementation of modal processors, which involve the parallel combination resonant filters, may be costly for applications such as artificial reverberation that can require thousands of modes. In one embodiment, the input signal is decomposed into a plurality of subbands, the outputs of which are downsampled. In each downsampled band, resonant filters are applied at the downsampled sampling rate, and their output is upsampled and filtered to form the band output. In these and other embodiments, a feature of responses of the mode filters have been optimized to minimize an aspect of a residual error after a point in time.

The method for adapting a sound converter to a reference sound converter includes the sound converter having a first linear transfer function with a first frequency response, a second linear transfer function with a second frequency response, and a trivial nonlinearity. The sound converter has a non-linear transfer function corresponding to the frequency response from combination of the first linear transfer function, the trivial nonlinearity, and the second linear transfer function. A first frequency spectrum of the reference sound converter is determined at a low input level. A second frequency spectrum of the reference sound converter is determined at a high input level. The second determined frequency spectrum is used as the second frequency response in the second linear transfer function, and the division of the first frequency spectrum by the second frequency spectrum is used as the first frequency response in the first linear transfer function.