| Name | brnolm JSON |
| Version |
0.3.0
JSON |
| download |
| home_page | |
| Summary | A language modeling toolit |
| upload_time | 2022-12-19 13:47:41 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.6 |
| license | MIT License Copyright (c) 2020 Karel Benes Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
language
modeling
|
| VCS |
|
| bugtrack_url |
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| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
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# BrnoLM
A neural language modeling toolkit built on PyTorch.
This is a scientific piece of code, so expect rough edges.
BrnoLM has so far powered language modeling in the following papers:
* Beneš et al. [Text Augmentation for Language Models in High Error Recognition Scenario](https://arxiv.org/pdf/2011.06056.pdf)
* Žmolíková et al. [BUT System for CHiME-6 Challenge](https://www.fit.vutbr.cz/research/groups/speech/publi/2020/zmolikova_CHiME_2020_abstract.pdf)
* Beneš et al. [i-vectors in language modeling: An efficient way of domain adaptation for feed-forward models](http://www.fit.vutbr.cz/research/groups/speech/publi/2018/benes_interspeech2018_1070.pdf)
* Beneš et al. [Unsupervised Language Model Adaptation for Speech Recognition with no Extra Resources](http://www.fit.vutbr.cz/research/groups/speech/publi/2019/benes_DAGA_2019.pdf)
## Installation
To install, clone this repository and exploit the provided `setup.py`, e.g.:
```
git clone git@github.com:BUTSpeechFIT/BrnoLM.git
cd BrnoLM
pip install . # or, if you don't care about environmental pollution: python setup.py install
```
If you want to edit the sources, [pip with `-e`](https://pip.pypa.io/en/stable/reference/pip_install/#editable-installs) or [setup.py develop](https://setuptools.readthedocs.io/en/latest/setuptools.html#development-mode).
Occasionally, a PIP version is produced, so you can simply `pip install brnolm` to obtain the last pre-packed version.
### Requirements
The above way of installation takes care of dependencies.
If you want to prepare an environment yourself, know that BrnoLM requires:
```
torch
numpy
scikit-learn
```
Exact tested versions are provided in `setup.py`.
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