monocleaner 1.2

Monolingual corpus fluency filter

monocleaner

Monocleaner is a Python tool that aims to detect disfluent sentences in a monolingual corpus. Each sentence is assigned a fluency score between 0 and 1, with higher scores indicating more fluency. In addition to a continuous score, several handwritten rules assign a score of 0 to obviously poor sentences.

Although a training tool (monocleaner-train) is provided, you may want to use the available ready-to-use language packages. Please, visit https://github.com/bitextor/monocleaner-data/releases/latest or use monocleaner-download to download the latest language packages.

Citation

If you find Monocleaner useful, please consider citing the following papers:

V. M. Sánchez-Cartagena, M. Bañón, S. Ortiz-Rojas and G. Ramírez-Sánchez,
"Prompsit's submission to WMT 2018 Parallel Corpus Filtering shared task",
in Proceedings of the Third Conference on Machine Translation, Volume 2: Shared Task Papers.
Brussels, Belgium: Association for Computational Linguistics, October 2018

@InProceedings{prompsit:2018:WMT,
  author    = { V\'{i}ctor M. S\'{a}nchez-Cartagena and Marta Ba{\~n}\'{o}n and Sergio Ortiz-Rojas and Gema Ram\'{i}rez-S\'{a}nchez},
  title     = {Prompsit's submission to WMT 2018 Parallel Corpus Filtering shared task},
  booktitle = {Proceedings of the Third Conference on Machine Translation, Volume 2: Shared Task Papers},
  month     = {October},
  address   = {Brussels, Belgium},
  publisher = {Association for Computational Linguistics}
}

Installation & Requirements

Monocleaner can be installed using pip:

python3.7 -m pip install monocleaner

Monocleaner requires the KenLM Python bindings with support for 7-gram language models. You can easily install it by running the following commands:

git clone https://github.com/kpu/kenlm
cd kenlm
python3.7 -m pip install . --install-option="--max_order 7"
mkdir -p build && cd build
cmake .. -DKENLM_MAX_ORDER=7 -DCMAKE_INSTALL_PREFIX:PATH=/your/prefix/path
make -j all install

The remaining extra modules required by Monocleaner will be automatically downloaded and installed/upgraded (if required) with the first command.

After installation, two binary files (monocleaner-train and monocleaner) will be located in your python/installation/prefix/bin directory. This is usually $HOME/.local/bin or /usr/local/bin/.

Monocleaner uses FastSpell that requires python-dev and libhunspell-dev:

sudo apt install python-dev libhunspell-dev

Also note that Hunspell language packages must be installed by hand if you are going to work with one of languages listed as similar, i.e.:

sudo apt-get install hunspell-es

or downloaded from an external source, such as https://github.com/wooorm/dictionaries/tree/main/dictionaries

You can also provide the path to the Hunspell dictionaries directories by using the dictpath atribute in {/YOUR/INSTALLATION/PATH}/config/hunspell.yaml (for example, venv/lib/python3.7/site-packages/fastspell/config/hunspell.yaml ) if you are installing from PyPI or with setup.py, or in /config/hunspell.yaml if you are running directly the code. Default path is /usr/share/hunspell.

Scoring

monocleaner aims to detect disfluent sentences in a monolingual corpus. Each sentence is assigned a fluency score between 0 and 1, with higher scores indicating more fluency. In addition to a continuous score, several handwritten hardrules assign a score of 0 to obviously poor sentences.

The input file (monolingual corpus) must contain one sentence per line text. The generated output file will contain the same lines adding a column containing the Monocleaner fluency score.

This tool can be run with

monocleaner [-h]
            [--disable_minimal_length]
            [--disable_hardrules]
            [--score_only]
            [--annotated_output]
            [--add_lang_ident]
            [--debug]
            [-q]
            model_dir [input] [output]

If input and output are omitted, it will read from stdin and write to stdout.

Parameters

• Positional arguments:
  • model_dir: Directory where the model is stored.
  • input: Input text file, one sentence per line. When omitted jointly with output, it will read from stdin.
  • output: Output tab-separated text file adding monocleaner score. When omitted output will be written to stdout.
• Optional arguments:
  • --score_only: Only output one column which is the monocleaner score (default: False)
  • --add_lang_ident: Add another column with the identified language if it's not disabled.
  • --disable_hardrules: Disables the hardrules filtering (only monocleaner fluency scoring is applied) (default: False)
  • --disable_minimal_length : Don't apply minimal length rule (default: False).
• Logging:
  • -q, --quiet: Silent logging mode (default: False)
  • --debug: Debug logging mode (default: False)
  • -v, --version: show version of this script and exit

Example

monocleaner models/es mono.es.txt mono.es.scored.txt

This will use the Spanish model located at models/es, read mono.es.txt file and write the sentences to mono.es.scored.txt adding the monocleaner score column.

---

All documents and software contained in this repository reflect only the authors' view. The Innovation and Networks Executive Agency of the European Union is not responsible for any use that may be made of the information it contains.