Metadata-Version: 2.1
Name: indicate
Version: 0.0.5
Summary: Transliterations to/from Indian languages
Home-page: https://github.com/in-rolls/indicate
Author: Rajashekar Chintalapati, Gaurav Sood
Author-email: rajshekar.ch@gmail.com, gsood07@gmail.com
License: MIT
Keywords: transliterate indic hindi english
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Utilities
Provides-Extra: dev
Provides-Extra: test
License-File: LICENSE

==================================================
Indicate: Transliterate Indic Languages to English
==================================================

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Transliterations to/from Indian languages are still generally low quality. One problem is access to data. Another is that there is no standard  transliteration.
For Hindi--English, we build novel dataset for names using the ESPNcricinfo. For instance, see `here <https://www.espncricinfo.com/hindi/series/pakistan-tour-of-england-2021-1239529/england-vs-pakistan-1st-odi-1239537/full-scorecard>`__ for hindi version of the `english scorecard <https://www.espncricinfo.com/series/pakistan-tour-of-england-2021-1239529/england-vs-pakistan-1st-odi-1239537/full-scorecard>`__.
We also create a dataset from `election affidavits <https://affidavit.eci.gov.in/CandidateCustomFilter>`__
We also exploit the `Google Dakshina dataset <https://github.com/google-research-datasets/dakshina>`__.

To overcome the fact that there isn't one standard way of transliteration, we provide k-best transliterations.

Install
-------
We strongly recommend installing `indicate` inside a Python virtual environment
(see `venv documentation <https://docs.python.org/3/library/venv.html#creating-virtual-environments>`__)

::

    pip install indicate

General API
-----------
1. transliterate.hindi2english will take Hindi text and translate into English.

Examples
--------
::

  from indicate import transliterate
  english_translated = transliterate.hindi2english("हिंदी")
  print(english_translated)

output -
hindi

Functions
----------
We expose 1 function, which will take Hindi text and transliterate it to English.

- **transliterate.hindi2english(input)**

  - What it does:

    - Converts given hindi text into English alphabet

  - Output

    - Returns text in English

Data
----
The datasets used to train the model:

- `Indian Election affidavits <https://affidavit.eci.gov.in/CandidateCustomFilter>`__

- `Google Dakshina dataset <https://github.com/google-research-datasets/dakshina>`__

- `ESPN Cric Info <https://www.espncricinfo.com/hindi/series/pakistan-tour-of-england-2021-1239529/england-vs-pakistan-1st-odi-1239537/full-scorecard>`__ for hindi version of the `english scorecard <https://www.espncricinfo.com/series/pakistan-tour-of-england-2021-1239529/england-vs-pakistan-1st-odi-1239537/full-scorecard>`__.

- `IIT Bombay English-Hindi Corpus <https://www.cfilt.iitb.ac.in/iitb_parallel/>`__

Evaluation
----------
Model was evaluated on test dataset of Google Dakshina dataset, Model predicted 73.64% exact matches.
`Indic-trans <https://github.com/libindic/indic-trans>`__ predicted 63.12% exact matches on Google Dakshina dataset.
Below is the edit distance metrics on test dataset (0.0 mean exact match, the farther away from 0.0,
the difference is more between predicted text and actual text)

.. image:: https://github.com/in-rolls/indicate/raw/master/images/h2e_ed.png
   :width: 400
   :alt: Edit distance metrics of model on Google Dakshina test dataset


Authors
-------

Rajashekar Chintalapati and Gaurav Sood

Contributor Code of Conduct
---------------------------------

The project welcomes contributions from everyone! In fact, it depends on
it. To maintain this welcoming atmosphere, and to collaborate in a fun
and productive way, we expect contributors to the project to abide by
the `Contributor Code of
Conduct <http://contributor-covenant.org/version/1/0/0/>`__.

License
----------

The package is released under the `MIT
License <https://opensource.org/licenses/MIT>`__.


