Metadata-Version: 2.1
Name: mosqito
Version: 0.2.1
Summary: Modular Sound Quality Integrated Toolbox
Home-page: https://github.com/Eomys/MoSQITo
Author: MoSQITo Developers
Author-email: martin.glesser@eomys.com
License: UNKNOWN
Download-URL: https://github.com/Eomys/MoSQITo/archive/v0.2.1.tar.gz
Description: # ![MOSQITO Logo](https://raw.githubusercontent.com/Eomys/MoSQITo/master/logo.png) MOSQITO
        
        ## Background
        
        Sound quality (SQ) metrics are developed by acoustic engineers and
        researchers to provide an objective assessment of the pleasantness of a
        sound. Different metrics exist depending on the nature of the sound to
        be tested. Some of these metrics are already standardized, while some
        others rely on scientific articles and are still under active
        development. The calculation of some sound quality metrics are included
        in major commercial acoustic and vibration measurement and analysis
        software. However, some of the proposed metrics results from in-house
        implementation and can be dependent from one system to another. Some
        implementations may also lack of complete documentation and validation
        on publicly available standardized sound samples. Several
        implementations of SQ metrics in different languages can been found
        online, confirming the interest of the engineering and scientific
        community, but they often use Matlab signal processing commercial
        toolbox.
        
        ## Objectives
        
        The objective of MOSQITO is therefore to provide a unified and modular
        development framework of key sound quality metrics with open-source
        object-oriented technologies, favoring reproducible science and
        efficient shared scripting among engineers, teachers and researchers
        community.
        
        It is written in Python, one of the most popular free programming
        language in the scientific computing community. It is meant to be highly
        documented (use of Jupyter notebooks, tutorials) and validated with
        reference sound samples and scientific publications.
        
        ## Origin of the project
        
        [EOMYS ENGINEERING](https://eomys.com/?lang=en) initiated this open-source project 
        in 2020 for the study of electric motor sound quality. The project is now
        backed by [Green Forge Coop](https://www.linkedin.com/company/greenforgecoop/) non profit organization, 
        who also supports the development of [Pyleecan](https://www.pyleecan.org) electrical 
        machine simulation software.
        
        ## Documentation
        
        Tutorials are available in the [tutorials](./tutorials/) folder. Documentation 
        and validation of the MOSQITO functions are available in the [documentation](./documentation/) folder.
        
        ## Scope
        
        The scope of the project is to implement the following first set of
        metrics:
        
        |                                                    | Reference                                            | Validated                                          | Available                                     | Under dev. | To do |
        |:-------------------------------------------------- |:---------------------------------------------------- |:--------------------------------------------------:|:---------------------------------------------:|:----------:|:-----:|
        | Loudness for<br>steady signals<br>(Zwicker method) | ISO 532B:1975<br>DIN 45631:1991<br>ISO 532-1:2017 §5 | [x](./mosqito/validations/loudness_zwicker/output) | [x](./documentation/loudness-stationary.md)   |            |       |
        | Loudness for non-stationary<br>(Zwicker method)    | DIN 45631/A1:2010<br>ISO 532-1:2017 §6               | [x](./mosqito/validations/loudness_zwicker/output) | [x](./documentation/loudness-time-varying.md) |            |       |
        | Roughness                                          | Daniel and Weber, 1997                               | [x](./mosqito/validations/roughness_danielweber)   | [x](./documentation/roughness.md)             |            |       |
        | Fluctuation Strength                               | To be defined                                        |                                                    |                                               |            | x     |
        | Sharpness                                          | DIN 45692:2009                                       | [x](./mosqito/validations/sharpness/output)        | [x](./documentation/sharpness.md)             |            |       |
        | Tonality (Hearing model)                           | ECMA-74:2019 annex G                                 |                                                    |                                               | x          |       |
        
        As a second priority, the project could address the following metrics:
        
        |                                                                                     | Reference                             | Validated | Available | Under dev. | To do |
        |:----------------------------------------------------------------------------------- |:------------------------------------- |:---------:|:---------:|:----------:|:-----:|
        | Loudness for steady signals<br>(Moore/Glasberg method)                              | ISO 532-2:2017                        |           |           |            | x     |
        | Loudness for non-stationary<br>(Moore/Glasberg method)                              | Moore, 2014                           |           |           |            | x     |
        | Sharpness (using <br>Moore/Glasberg loudness)                                       | Hales-Swift<br>and Gee, 2017          |           |           |            | x     |
        | Tone-to-noise ratio / Prominence <br> ratio (occupational noise,<br>discrete tones) | ECMA-74:2019 annex D<br>ISO 7719:2018 |           | x         |            |       |
        | Tone-to-noise ratio<br>(environmental noise,<br>automatic tone detection)           | DIN 45681                             |           |           |            | x     |
        | Tone-to-noise ratio<br>(environmental noise)                                        | ISO 1996-2                            |           |           |            | x     |
        | Tone-to-noise ratio<br>(environmental noise)                                        | ANSI S1.13:2005                       |           |           |            | x     |
        
        In parallel, tools for signal listening and manipulation will be
        developed. The objective is to be able to apply some modification to a
        signal (filtering, tone removal, etc.) and assess the impact on
        different SQ metrics.
        
        Of course, any other sound quality related implementation by anyone who
        wants to contribute is welcome.
        
        ## Contact
        
        You can contact us on Github by opening an issue (to request a feature,
        ask a question or report a bug).
        
        ## References
        
        Daniel, P., and Weber, R. (1997). “Psychoacoustical Roughness: Implementation 
        of an Optimized Model”, Acta Acustica, Vol. 83: 113-123
        
        Hales Swift, S., and Gee, K. L. (2017). “Extending sharpness calculation
        for an alternative loudness metric input,” J. Acoust. Soc. Am.142,
        EL549. 
        
        Moore, B. C. J. (2014). “Development and Current Status of the
        “Cambridge” Loudness Models,” Trends in Hearing, vol. 18: 1-29
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >= 3.5
Description-Content-Type: text/markdown
Provides-Extra: testing
