语言:

• 荷兰语 标签:
• 标点预测
• 标点符号 数据集: sonar 许可证: mit 小部件:
• 文本: "Ondanks dat het nu bijna voorjaar is hebben we nog steds best koude dagen" 示例标题: "荷兰语样本" 指标:
• f1分数

该模型用于预测荷兰语文本的标点符号。我们开发此模型旨在恢复转录口语的标点符号。

此模型基于SoNaR数据集训练而成。

模型可恢复以下标点符号：“.” “,” “?” “-” “:”

示例代码

我们提供了一个简单的Python包，可处理任意长度的文本。

安装

从pypi安装包以开始使用：

pip install deepmultilingualpunctuation

恢复标点符号

from deepmultilingualpunctuation import PunctuationModel

model = PunctuationModel(model="oliverguhr/fullstop-dutch-sonar-punctuation-prediction")
text = "hervatting van de zitting ik verklaar de zitting van het europees parlement die op vrijdag 17 december werd onderbroken te zijn hervat"
result = model.restore_punctuation(text)
print(result)

输出

hervatting van de zitting. ik verklaar de zitting van het europees parlement, die op vrijdag 17 december werd onderbroken, te zijn hervat.

预测标签

from deepmultilingualpunctuation import PunctuationModel

model = PunctuationModel(model="oliverguhr/fullstop-dutch-sonar-punctuation-prediction")
text = "hervatting van de zitting ik verklaar de zitting van het europees parlement die op vrijdag 17 december werd onderbroken te zijn hervat"
clean_text = model.preprocess(text)
labled_words = model.predict(clean_text)
print(labled_words)

输出

[['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]]

结果

不同标点符号的性能表现有所差异，因为连字符和冒号在许多情况下是可选的，可以用逗号或句号替代。模型达到的F1分数如下：

语言

模型

社区模型

可通过设置模型参数使用不同模型：

model = PunctuationModel(model = "oliverguhr/fullstop-dutch-punctuation-prediction")

如何引用我们

@misc{https://doi.org/10.48550/arxiv.2301.03319,
  doi = {10.48550/ARXIV.2301.03319},
  url = {https://arxiv.org/abs/2301.03319},
  author = {Vandeghinste, Vincent and Guhr, Oliver},
  keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences, I.2.7},
  title = {FullStop:Punctuation and Segmentation Prediction for Dutch with Transformers},
  publisher = {arXiv},
  year = {2023},  
  copyright = {Creative Commons Attribution Share Alike 4.0 International}
}