Metadata-Version: 2.1
Name: scikit-talk
Version: 0.0.223
Summary: Scikit-talk helps to process real-world conversational speech data.
Home-page: https://github.com/partigabor/scikit_talk
Author: Gabor Parti
Author-email: gabor.parti@connect.polyu.hk
License: MIT license
Keywords: scikit_talk
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: AUTHORS.rst
Requires-Dist: Click (>=7.0)
Requires-Dist: speach (>=0.1a9.post2)
Requires-Dist: pylangacq (>=0.15.0)

===========
scikit-talk
===========


.. image:: https://img.shields.io/pypi/v/scikit_talk.svg
        :target: https://pypi.python.org/pypi/scikit_talk

.. image:: https://img.shields.io/travis/partigabor/scikit_talk.svg
        :target: https://travis-ci.com/partigabor/scikit_talk

.. image:: https://readthedocs.org/projects/scikit-talk/badge/?version=latest
        :target: https://scikit-talk.readthedocs.io/en/latest/?version=latest
        :alt: Documentation Status



Scikit-talk helps to process real-world conversational speech data.

Scikit-talk is a free and open source Python library to help working with transcriptions of conversational speech data, tailored for the research community.
The ultimate aim is to make the processing, analyzing, and merging of such corpora speedier, and less cumbersome.
Scikit-talk is still in development, with various modules underway. The current version features a working Preprocessor module.

Preprocessor module - build dataframes from files (e.g. .eaf, .cha, .txt).
This module currently contains 3 functions. They essentially execute similar tasks for different transcription formats.
The functions read in differently formatted conversational speech data, returning them in a unified format, which is then comparable, concatenatable,
and easier to work on.

The functions of the Preprocessor module take two arguments, an input path, and an output path, where the latter is optional.
If an output path is given, a .csv file is written there, which contains the a dataframe of all the transcription files that were read in.
If only an input file is given, the functions return a dataframe compiled from the files.

The data is organized into the following columns: begin, end, speaker, utterance, source.
If the corpus provides timestamps, begin and end will contain these in a pandas.datetime format, otherwise NaN.

We assume that the corpora and files are formatted perfectly, adhering to the requirements of various standards and conventions (e.g. Linguistic Data Consortium).

* Free software: MIT license
* Documentation: https://scikit-talk.readthedocs.io.
* GitHub: https://github.com/partigabor/scikit_talk

Features
--------

* Preprocessor

Credits
-------
This package uses tools from the speach_ library made by Le Tuan Anh, and the pylangacq_ library by Jackson L. Lee.
This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _speach: https://github.com/neocl/speach
.. _pylangacq: https://github.com/jacksonllee/pylangacq
.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage


=======
History
=======

0.0.223 (2021-07-27)
------------------

* First release on PyPI.


