# Compute emotion expression-related voice features
[](https://github.com/mexca/emvoice)
[](https://www.research-software.nl/software/emvoice)
[](https://zenodo.org/badge/latestdoi/665993095)
[](https://fair-software.eu)
[](https://sonarcloud.io/dashboard?id=mexca_emvoice)
[](https://sonarcloud.io/dashboard?id=mexca_emvoice)
[](https://emvoice.readthedocs.io/en/latest/?badge=latest)
[](https://github.com/mexca/emvoice/actions/workflows/build.yml)
[](https://github.com/mexca/emvoice/actions/workflows/cffconvert.yml)
[](https://github.com/mexca/emvoice/actions/workflows/sonarcloud.yml)
[](https://github.com/mexca/emvoice/actions/workflows/markdown-link-check.yml)
[](https://github.com/psf/black)
## How to use emvoice
**emvoice** is a pure Python package for computing emotion expression-related features from speech signals. It uses similar algorithms as in [Praat](https://www.praat.org) and [openSMILE](https://github.com/audeering/opensmile/) but also includes more recent methods from the [librosa](https://librosa.org/doc/latest/index.html) package. Currently, most low-level descriptor features from the extended Geneva Minimalistic Acousting Parameter Set ([eGeMAPS](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7160715)) are implemented.
Given that it is entirely written in Python, it is easier to include emvoice in other Python-based applications, especially if they use numpy or scipy.
## Getting started
Take a look at the [examples](https://emvoice.readthedocs.io/en/latest/examples.html) to get started with emvoice.
## Installation
emvoice requires Python >=3.7 and can be installed via `pip`:
```console
pip install emvoice
```
To install the lastet development version from GitHub repository, do:
```console
git clone https://github.com/mexca/emvoice.git
cd emvoice
python -m pip install .
```
## Documentation
The documentation of emvoice can be found on [Read the Docs](https://emvoice.readthedocs.io/en/latest/index.html).
## Contributing
If you want to contribute to the development of emvoice,
have a look at the [contribution guidelines](CONTRIBUTING.md).
## Credits
This package was created with [Cookiecutter](https://github.com/audreyr/cookiecutter) and the [NLeSC/python-template](https://github.com/NLeSC/python-template).
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