Skip to main content

NeMo text processing for ASR and TTS

Project description

NeMo Text Processing

Introduction

nemo-text-processing is a Python package for text normalization and inverse text normalization.

Documentation

NeMo-text-processing (text normalization and inverse text normalization).

Tutorials

Google Collab Notebook Description
Text_(Inverse)_Normalization.ipynb Quick-start guide
WFST_Tutorial In-depth tutorial on grammar customization

Getting help

If you have a question which is not answered in the Github discussions, encounter a bug or have a feature request, please create a Github issue. We also welcome you to directly open a pull request to fix a bug or add a feature.

Installation

Conda virtual environment

We recommend setting up a fresh Conda environment to install NeMo-text-processing.

conda create --name nemo_tn python==3.10
conda activate nemo_tn

(Optional) To use hybrid text normalization install PyTorch using their configurator.

conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch

NOTE: The command used to install PyTorch may depend on your system.

Pip

Use this installation mode if you want the latest released version.

pip install nemo_text_processing

NOTE: This should work on any Linux OS with x86_64. Pip installation on MacOS and Windows are not supported due to the dependency Pynini. On a platform other than Linux x86_64, installing from Pip tries to compile Pynini from scratch, and requires OpenFst headers and libraries to be in the expected place. So if it's working for you, it's because you happen to have installed OpenFst in the right way in the right place. So if you want to Pip install Pynini on MacOS, you have to have pre-compiled and pre-installed OpenFst. The Pynini README for that version should tell you which version it needs and what --enable-foo flags to use. Instead, we recommend you to use conda-forge to install Pynini on MacOS or Windows: conda install -c conda-forge pynini=2.1.6.post1.

Pip from source

Use this installation mode if you want the a version from particular GitHub branch (e.g main).

pip install Cython
python -m pip install git+https://github.com/NVIDIA/NeMo-text-processing.git@{BRANCH}#egg=nemo_text_processing

From source

Use this installation mode if you are contributing to NeMo-text-processing.

git clone https://github.com/NVIDIA/NeMo-text-processing
cd NeMo-text-processing
./reinstall.sh

NOTE: If you only want the toolkit without additional conda-based dependencies, you may replace reinstall.sh with pip install -e . with the NeMo-text-processing root directory as your current working director.

Contributing

We welcome community contributions! Please refer to the CONTRIBUTING.md for guidelines.

Citation

@inproceedings{zhang21ja_interspeech,
  author={Yang Zhang and Evelina Bakhturina and Boris Ginsburg},
  title={{NeMo (Inverse) Text Normalization: From Development to Production}},
  year=2021,
  booktitle={Proc. Interspeech 2021},
  pages={4857--4859}
}

@inproceedings{bakhturina22_interspeech,
  author={Evelina Bakhturina and Yang Zhang and Boris Ginsburg},
  title={{Shallow Fusion of Weighted Finite-State Transducer and Language Model for
Text Normalization}},
  year=2022,
  booktitle={Proc. Interspeech 2022}
}

License

NeMo-text-processing is under Apache 2.0 license.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

nemo_text_processing-1.2.0.tar.gz (1.9 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

nemo_text_processing-1.2.0-py3-none-any.whl (3.3 MB view details)

Uploaded Python 3

File details

Details for the file nemo_text_processing-1.2.0.tar.gz.

File metadata

  • Download URL: nemo_text_processing-1.2.0.tar.gz
  • Upload date:
  • Size: 1.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.0

File hashes

Hashes for nemo_text_processing-1.2.0.tar.gz
Algorithm Hash digest
SHA256 b28dfcf1bb336ea9e263557fc7a36546d6eeb1fa4d62add1e58d531651ba2533
MD5 c6a2b68a33524cba8d6181da06361f88
BLAKE2b-256 254368b08e95f1afcf6ad58485d55642c86c41befcb557bed5b8daf60ef12222

See more details on using hashes here.

File details

Details for the file nemo_text_processing-1.2.0-py3-none-any.whl.

File metadata

File hashes

Hashes for nemo_text_processing-1.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 dd78657a0f031023de8b2c8fee6b55d71f444485826f7b507881e407afa5d804
MD5 9d1ab6a73513087eb0e9ca4182f3da05
BLAKE2b-256 b608ca954a6b77d259561f56580adfd52eb69f54dc2469e1184157708480e7ed

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page