monocleaner 1.1.1

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.

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