A simple, deterministic, and extensible approach to inverse text normalization for numbers
Project description
Inverse Text Normalization
.. raw:: html
A simple, deterministic, and extensible approach to
inverse text normalization <https://www.google.com/search?q=inverse+text+normalization>
_
(ITN) for numbers.
Overview
This package converts raw spoken-form text (speech recognition output) into
user-friendly written-form text. It works best for converting spoken numbers
into numerical digits, or other translation tasks that do not modify word ordering.
A csv <https://github.com/barseghyanartur/itnpy/blob/master/assets/vocab.csv>
_
file is provided to define the basic rules for transforming spoken tokens into
written tokens, and extra pre/post-processing may be applied for more specific
formatting requirements, i.e. dates, measurements, money, etc.
.. raw:: html
.. raw:: html
Installation
This package supports Python versions >= 3.7
To install from pypi <https://pypi-hypernode.com/project/itnpy2>
_\ :
.. code-block:: shell
$ pip install itnpy2
To install locally:
.. code-block:: shell
$ pip install -e .
Tests
To run tests, use pytest
in the root folder of this repository:
.. code-block:: shell
$ ls LICENSE assets scripts src README.md requirements.txt setup.py tests
$ pytest
Issues
This package has been verified on a limited set of
test-cases <https://github.com/barseghyanartur/itnpy/tree/master/tests/assets/>
.
For any translation mistakes, feel free to open a pull request and update
failing.csv <https://github.com/barseghyanartur/itnpy/blob/master/tests/assets/inverse_normalize_numbers/failing.csv>
with the input, expected output, and mistake; thanks!
Citation
If you find this work useful, please consider citing it.
.. code-block:: text
@misc{hsu2022itn, title = {A simple, deterministic, and extensible approach to inverse text normalization for numbers}, author = {Brandhsu}, howpublished = {https://github.com/barseghyanartur/itnpy}, year = {2022} }
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