lim-sample
Implementation of SAMPLE (Spectral Analysis for Modal Parameter Linear Estimate)
Science Score: 67.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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✓DOI references
Found 4 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
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○Scientific vocabulary similarity
Low similarity (14.7%) to scientific vocabulary
Keywords
Repository
Implementation of SAMPLE (Spectral Analysis for Modal Parameter Linear Estimate)
Basic Info
- Host: GitHub
- Owner: LIMUNIMI
- License: mit
- Language: Python
- Default Branch: main
- Homepage: https://limunimi.github.io/SAMPLE/
- Size: 3.21 MB
Statistics
- Stars: 8
- Watchers: 3
- Forks: 0
- Open Issues: 1
- Releases: 0
Topics
Metadata Files
README.md
Spectral Analysis for Modal Parameter Linear Estimate
Python package with tools for spectral analysis and modal parameters estimate
Table of Contents
Install
We recommend installing in a virtual environment. For how to create virtual environments, please, refer to the official documentation for venv or conda.
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
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.exefile - That's it, you can run it!
Python
You can install the GUI from the command line with Python via pip.
We recommend to install in a virtual environment
pip install lim-sample[gui]
To run the GUI from the command line, run
python -m sample.gui
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
Scripts
In the scripts folder, there are Python scripts for the reproducibility of experiments
References
References are available both as a BibTeX and a CITATION.cff file.
If you use this software in your research, please, consider citing the following items - The SMC 2020 paper "Spectral Analysis for Modal Parameters Linear Estimate" - The SAMPLE package for Python
Owner
- Name: Laboratorio di Informatica Musicale
- Login: LIMUNIMI
- Kind: organization
- Website: http://www.lim.di.unimi.it/
- Repositories: 12
- Profile: https://github.com/LIMUNIMI
Citation (CITATION.cff)
abstract: "Python package with tools for spectral analysis and modal parameters estimate"
authors:
- affiliation: "LIM, Department of Computer Science, University of Milan"
alias: "ChromaticIsobar"
city: "Milan"
country: "IT"
email: "marco.tiraboschi@unimi.it"
family-names: "Tiraboschi"
given-names: "Marco"
orcid: "https://orcid.org/0000-0001-5761-4837"
cff-version: 1.2.0
contact:
- affiliation: "LIM, Department of Computer Science, University of Milan"
alias: "ChromaticIsobar"
city: "Milan"
country: "IT"
email: "marco.tiraboschi@unimi.it"
family-names: "Tiraboschi"
given-names: "Marco"
orcid: "https://orcid.org/0000-0001-5761-4837"
doi: "10.5281/zenodo.6536419"
keywords:
- "audio analysis"
- "parameter estimation"
- "physical modelling"
license: "MIT"
message: "If you use this software in your research, please, cite the appropriate references from this file"
references:
- abbreviation: SAMPLE (SMC 2020)
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."
authors:
- affiliation: "LIM, Department of Computer Science, University of Milan"
alias: "ChromaticIsobar"
city: "Milan"
country: "IT"
email: "marco.tiraboschi@unimi.it"
family-names: "Tiraboschi"
given-names: "Marco"
orcid: "https://orcid.org/0000-0001-5761-4837"
- affiliation: "LIM, Department of Computer Science, University of Milan"
city: "Milan"
country: "IT"
email: "federico.avanzini@unimi.it"
family-names: "Avanzini"
given-names: "Federico"
orcid: "https://orcid.org/0000-0002-1257-5878"
website: "http://homes.di.unimi.it/avanzini"
- affiliation: "LIM, Department of Computer Science, University of Milan"
city: "Milan"
country: "IT"
email: "stavros.ntalampiras@unimi.it"
family-names: "Ntalampiras"
given-names: "Stavros"
orcid: "https://orcid.org/0000-0003-3482-9215"
collection-doi: "10.5281/zenodo.3903573"
collection-title: "Proceedings of the 17th Sound and Music Computing Conference"
collection-type: "proceedings"
conference:
- alias: "SMC 2020"
city: "Torino"
country: "IT"
date-end: "2020-06-26"
date-start: "2020-06-24"
name: "Sound and Music Computing Conference"
website: "https://smcnetwork.org"
copyright: "©2020 Marco Tiraboschi et al."
date-published: "2020-06-17"
doi: "10.5281/zenodo.3898795"
editors:
- family-names: "Spagnol"
given-names: "Simone"
- family-names: "Valle"
given-names: "Andrea"
end: 283
isbn: "978-88-945415-0-2"
issn: "2518-3672"
license: "CC-BY-3.0"
month: 6
pages: 8
publisher: "Axea sas/SMC Network"
repository: "https://gitlab.com/ChromaticIsobar/pyaprsi2"
start: 276
title: "Spectral Analysis for Modal Parameters Linear Estimate"
type: "proceedings"
year: 2020
repository-code: "https://github.com/limunimi/sample"
title: "SAMPLE"
type: "software"
url: "https://limunimi.github.io/SAMPLE"
GitHub Events
Total
- Watch event: 2
Last Year
- Watch event: 2
Committers
Last synced: about 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Marco Tiraboschi | m****i@h****t | 640 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 1
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 1
- Total pull request authors: 0
- Average comments per issue: 0.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- ChromaticIsobar (1)
Pull Request Authors
Top Labels
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Packages
- Total packages: 1
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Total downloads:
- pypi 45 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 39
- Total maintainers: 1
pypi.org: lim-sample
Package for the SAMPLE method
- Homepage: https://github.com/limunimi/sample
- Documentation: https://lim-sample.readthedocs.io/
- License: MIT License
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Latest release: 2.2.0
published almost 3 years ago