lim-sample 1.5.0a0

Package for the SAMPLE method

Spectral Analysis for Modal Parameter Linear Estimate

Install

You can install the sample package from PyPI via pip

pip install lim-sample

Available extras are

• plots: for plotting utilities
• notebooks: for running notebooks
• gui: for running the GUI

GUI

If you don't want write code to use SAMPLE, you can use the graphical user interface

Please, note that the GUI is still in its alpha release phase

Windows

For Windows, a stand-alone executable is available. You can download the latest version from GitHub:

• Go to https://github.com/limunimi/sample/releases
• Download the zip file from the latest release (SAMPLE_win_<version>.zip)
• Unzip the SAMPLE.exe file
• That's it, you can run it!

You can change the theme of the GUI (e.g. use a dark theme) this way:

• Create a shortcut to the SAMPLE.exe file (right-click on the file and select Create shortcut)
• Right-click on the shortcut and open Properties
• In the Shortcut tab, go to Target (it should be set to the path of the SAMPLE.exe file, e.g. C:\Users\User\Downloads\SAMPLE.exe)
• Add the theme option --theme <theme name> after the file path. E.g. if you want to use the theme equilux, you should add --theme equilux
• That's it, you can run it by clicking on the shortcut!

For a full list of supported themes go to ttkthemes.readthedocs.io.
The default theme for Windows is Arc. Suggested dark theme is Equilux.

Python

You can install the GUI from the command line with Python via pip.
It is recommended run these commands in a virtual environment in
order to to keep your system clean

pip install lim-sample[gui]==1.5.0a0

To run the GUI from the command line, run

python -m sample.gui

You can change the theme of the GUI (e.g. use a dark theme) by specifying a theme option

python -m sample.gui --theme <theme name>

E.g. if you want to use the theme equilux, you should run

python -m sample.gui --theme equilux

For a full list of supported themes go to ttkthemes.readthedocs.io.
The default theme is Radiance for Linux and Arc for all other systems.
Suggested dark theme is Equilux.

Documentation

API documentation can be found online here:

https://limunimi.github.io/SAMPLE/

Source code

Source code is available on GitHub

https://github.com/limunimi/sample

Notebooks

For learning to use the package, you can refer to the interactive notebooks in the notebooks folder

Paper

Your can find the paper in the SMC 2020 proceedings here.

Abstract

Modal synthesis is used to generate the sounds associated with the vibration of rigid bodies, according to the characteristics of the force applied onto the object. Towards obtaining sounds of high quality, a great quantity of modes is necessary, the development of which is a long and tedious task for sound designers as they have to manually write the modal parameters. This paper presents a new approach for practical modal parameter estimation based on the spectral analysis of a single audio example. The method is based on modelling the spectrum of the sound with a time-varying sinusoidal model and fitting the modal parameters with linear and semi-linear techniques. We also detail the physical and mathematical principles that motivate the algorithm design choices. A Python implementation of the proposed approach has been developed and tested on a dataset of impact sounds considering objects of different shapes and materials. We assess the performance of the algorithm by evaluating the quality of the resynthesised sounds. Resynthesis is carried out via the Sound Design Toolkit (SDT) modal engine and compared to the sounds resynthesised from parameters extracted by SDT's own estimator. The proposed method was thoroughly evaluated both objectively using perceptually relevant features and subjectively following the MUSHRA protocol.

Cite

@inproceedings{tiraboschi2020spectral,
	title={Spectral Analysis for Modal Parameters Linear Estimate},
	author={Tiraboschi, M and Avanzini, F and Ntalampiras, S},
	booktitle={Sound \& Music Computing Conference},
	year={2020},
	organization={SMC},
}