专为数学公式优化的语音朗读系统，让公式也能准确发音。
MathReader : Text-to-Speech for Mathematical Documents
- 结合OCR与微调T5模型，识别并理解公式语义
- 处理含公式的文档时，错误率降至0.281（原0.510~0.617）
- 适合视障用户或需听读学术论文的研究者
微软、Adobe、苹果和OpenAI等公司提供的文本转语音（TTS）文档阅读器已在全球广泛使用。它们对普通纯文本的朗读效果良好，但在处理数学表达式时常出现漏读或发音不准的问题。原因在于现代学术论文多用LaTeX撰写，公式在编译后以特殊文本形式呈现，而传统TTS仅按字符识别，未考虑公式语义。为此，我们提出MathReader，融合OCR、微调T5模型与TTS技术。在含数学公式的文档上，MathReader的词错误率（WER）显著低于现有系统：相比Microsoft Edge从0.510降至0.281，相比Adobe Acrobat从0.617降至0.281。该成果将极大改善视障用户及需要听读学术文献人群的体验。代码已开源：https://github.com/hyeonsieun/MathReader。
原文摘要 · Abstract (English)
TTS (Text-to-Speech) document reader from Microsoft, Adobe, Apple, and OpenAI have been serviced worldwide. They provide relatively good TTS results for general plain text, but sometimes skip contents or provide unsatisfactory results for mathematical expressions. This is because most modern academic papers are written in LaTeX, and when LaTeX formulas are compiled, they are rendered as distinctive text forms within the document. However, traditional TTS document readers output only the text as it is recognized, without considering the mathematical meaning of the formulas. To address this issue, we propose MathReader, which effectively integrates OCR, a fine-tuned T5 model, and TTS. MathReader demonstrated a lower Word Error Rate (WER) than existing TTS document readers, such as Microsoft Edge and Adobe Acrobat, when processing documents containing mathematical formulas. MathReader reduced the WER from 0.510 to 0.281 compared to Microsoft Edge, and from 0.617 to 0.281 compared to Adobe Acrobat. This will significantly contribute to alleviating the inconvenience faced by users who want to listen to documents, especially those who are visually impaired. The code is available at https://github.com/hyeonsieun/MathReader.
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