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Computer Science > Artificial Intelligence

arXiv:2501.07088 (cs)
[Submitted on 13 Jan 2025]

Title:MathReader : Text-to-Speech for Mathematical Documents

Authors:Sieun Hyeon, Kyudan Jung, Nam-Joon Kim, Hyun Gon Ryu,
Jaeyoung Do
View a PDF of the paper titled MathReader : Text-to-Speech for
Mathematical Documents, by Sieun Hyeon and 4 other authors
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    Abstract: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 this https URL.

Comments: Accepted at ICASSP 2025
Subjects: Artificial Intelligence (cs.AI); Sound (cs.SD); Audio and
          Speech Processing (eess.AS)
Cite as:  arXiv:2501.07088 [cs.AI]
          (or arXiv:2501.07088v1 [cs.AI] for this version)
          https://doi.org/10.48550/arXiv.2501.07088
          Focus to learn more
          arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Sieun Hyeon [view email]
[v1] Mon, 13 Jan 2025 06:47:05 UTC (1,457 KB)
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