论文标题
Simple-QE：简化文本的更好自动质量估计
Simple-QE: Better Automatic Quality Estimation for Text Simplification
论文作者
论文摘要
文本简化系统生成的文本版本对于更广泛的受众来说更容易理解。通常使用与人类参考的指标估算简化文本的质量，这很难获得。我们提出了Simple-QE，这是一个基于BERT的质量估计（QE）模型，该模型是根据先前的摘要量化量化量化量化量化量化量化量子标准的，并表明它与人类质量判断良好相关。 Simple-QE不需要人类参考，这使得该模型在实用环境中有用，在这种情况下，需要了解用户生成的简化质量。我们还表明，我们可以适应这种方法，以准确预测人写的文本的复杂性。
Text simplification systems generate versions of texts that are easier to understand for a broader audience. The quality of simplified texts is generally estimated using metrics that compare to human references, which can be difficult to obtain. We propose Simple-QE, a BERT-based quality estimation (QE) model adapted from prior summarization QE work, and show that it correlates well with human quality judgments. Simple-QE does not require human references, which makes the model useful in a practical setting where users would need to be informed about the quality of generated simplifications. We also show that we can adapt this approach to accurately predict the complexity of human-written texts.
