Batch deconvolve / process impulse response tool
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Updated
May 27, 2024 - Python
Batch deconvolve / process impulse response tool
Enhance Spotify with controls to save favourite snips, auto-skip tracks, and set global and custom speed. More to come!
Wave-based room acoustic modeling package with the DG method
Wave-based room acoustic modeling package with the DG method
This is the official implementation of our mesh-based neural network (MESH2IR) to generate acoustic impulse responses (IRs) for indoor 3D scenes represented using a mesh.
A dataset of filters for headphone correction and binaural synthesis of spatial audio systems on headphones
Local projection methods for impulse response estimation
Essential toolkits for working with autoregressive models
Binaural Room Reverb
Julia implementation of multi-variate time series models, such as vector autoregressive (VAR) and vector error correction (VECM) models.
Convolution Interactive Visualization is a tool for convolution of two signals. It lets the user visualize and calculate how the convolution of two functions is determined.
julia implementation of Smooth Local Projections (SLP)
Official code for "Learning Neural Acoustic Fields" (NeurIPS 2022)
WORK-IN-PROGRESS Solve and estimate heterogenous agent models with sequence-space Jacobians
Fast convolution and deconvolution functions using Fast Fourier Transform (FFT)
This is the official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.
Audio Processing with Python
A novel neural network for effective learning of highly impulsive/oscillatory dynamic systems by jointly utilizing low-order derivatives
A novel neural network for effective learning of highly impulsive/oscillatory dynamic systems by jointly utilizing low-order derivatives
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