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--- |
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language: |
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- nl |
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tags: |
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- punctuation prediction |
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- punctuation |
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datasets: sonar |
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license: mit |
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widget: |
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- text: "Ondanks dat het nu bijna voorjaar is hebben we nog steds best koude dagen" |
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example_title: "Dutch Sample" |
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metrics: |
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- f1 |
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--- |
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This model predicts the punctuation of Dutch texts. We developed it to restore the punctuation of transcribed spoken language. |
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This model was trained on the [SoNaR Dataset](http://hdl.handle.net/10032/tm-a2-h5). |
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The model restores the following punctuation markers: **"." "," "?" "-" ":"** |
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## Sample Code |
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We provide a simple python package that allows you to process text of any length. |
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## Install |
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To get started install the package from [pypi](https://pypi.org/project/deepmultilingualpunctuation/): |
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```bash |
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pip install deepmultilingualpunctuation |
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``` |
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### Restore Punctuation |
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```python |
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from deepmultilingualpunctuation import PunctuationModel |
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model = PunctuationModel(model="oliverguhr/fullstop-dutch-sonar-punctuation-prediction") |
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text = "hervatting van de zitting ik verklaar de zitting van het europees parlement die op vrijdag 17 december werd onderbroken te zijn hervat" |
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result = model.restore_punctuation(text) |
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print(result) |
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``` |
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**output** |
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> hervatting van de zitting. ik verklaar de zitting van het europees parlement, die op vrijdag 17 december werd onderbroken, te zijn hervat. |
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### Predict Labels |
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```python |
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from deepmultilingualpunctuation import PunctuationModel |
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model = PunctuationModel(model="oliverguhr/fullstop-dutch-sonar-punctuation-prediction") |
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text = "hervatting van de zitting ik verklaar de zitting van het europees parlement die op vrijdag 17 december werd onderbroken te zijn hervat" |
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clean_text = model.preprocess(text) |
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labled_words = model.predict(clean_text) |
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print(labled_words) |
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``` |
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**output** |
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> [['hervatting', '0', 0.99998724], ['van', '0', 0.9999784], ['de', '0', 0.99991274], ['zitting', '.', 0.6771242], ['ik', '0', 0.9999466], ['verklaar', '0', 0.9998566], ['de', '0', 0.9999783], ['zitting', '0', 0.9999809], ['van', '0', 0.99996245], ['het', '0', 0.99997795], ['europees', '0', 0.9999783], ['parlement', ',', 0.9908242], ['die', '0', 0.999985], ['op', '0', 0.99998224], ['vrijdag', '0', 0.9999831], ['17', '0', 0.99997985], ['december', '0', 0.9999827], ['werd', '0', 0.999982], ['onderbroken', ',', 0.9951485], ['te', '0', 0.9999677], ['zijn', '0', 0.99997723], ['hervat', '.', 0.9957053]] |
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## Results |
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The performance differs for the single punctuation markers as hyphens and colons, in many cases, are optional and can be substituted by either a comma or a full stop. The model achieves the following F1 scores: |
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| Label | F1 Score | |
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| ------------- | -------- | |
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| 0 | 0.985816 | |
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| . | 0.854380 | |
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| ? | 0.684060 | |
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| , | 0.719308 | |
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| : | 0.696088 | |
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| - | 0.722000 | |
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| macro average | 0.776942 | |
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| micro average | 0.963427 | |
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## Languages |
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### Models |
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| Languages | Model | |
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| ------------------------------------------ | ------------------------------------------------------------ | |
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| English, Italian, French and German | [oliverguhr/fullstop-punctuation-multilang-large](https://huggingface.co/oliverguhr/fullstop-punctuation-multilang-large) | |
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| English, Italian, French, German and Dutch | [oliverguhr/fullstop-punctuation-multilingual-sonar-base](https://huggingface.co/oliverguhr/fullstop-punctuation-multilingual-sonar-base) | |
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| Dutch | [oliverguhr/fullstop-dutch-sonar-punctuation-prediction](https://huggingface.co/oliverguhr/fullstop-dutch-sonar-punctuation-prediction) | |
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### Community Models |
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| Languages | Model | |
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| ------------------------------------------ | ------------------------------------------------------------ | |
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|English, German, French, Spanish, Bulgarian, Italian, Polish, Dutch, Czech, Portugese, Slovak, Slovenian| [kredor/punctuate-all](https://huggingface.co/kredor/punctuate-all) | |
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| Catalan | [softcatala/fullstop-catalan-punctuation-prediction](https://huggingface.co/softcatala/fullstop-catalan-punctuation-prediction) | |
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You can use different models by setting the model parameter: |
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```python |
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model = PunctuationModel(model = "oliverguhr/fullstop-dutch-punctuation-prediction") |
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``` |
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## How to cite us |
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``` |
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@misc{https://doi.org/10.48550/arxiv.2301.03319, |
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doi = {10.48550/ARXIV.2301.03319}, |
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url = {https://arxiv.org/abs/2301.03319}, |
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author = {Vandeghinste, Vincent and Guhr, Oliver}, |
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keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences, I.2.7}, |
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title = {FullStop:Punctuation and Segmentation Prediction for Dutch with Transformers}, |
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publisher = {arXiv}, |
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year = {2023}, |
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copyright = {Creative Commons Attribution Share Alike 4.0 International} |
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} |
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``` |
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