IU Incubator
Read-Aloud Maths

Exploring practical text-to-speech solutions for learning with mathematical content in higher education.

Projektbeschreibung

In June 2025, the EU Accessibility Act and the corresponding national Accessibility Improvement Act came into force. They require service providers to make products such as websites and e-books accessible to people with disabilities, e.g. visual impairments. Some exceptions apply, but, in practice, there is no full consensus yet which accessibility measures are sufficient to offer a good learning process for students with disabilities. One prominent aspect of accessibility is the presentation of contents in a way that they can be processed by assistive technology such as speech synthesis.

In fact, learning by listening does not only benefit students with disabilities, but is common among students of all cohorts. The IU Learning Report 2024 has established the broad usage of media such as podcasts and audio books among all age groups.

While the speech synthesis of plain texts has reached highly sophisticated levels for many years, the technology for reading mathematical formulas is still in its infancy. Though pipelines that convert text with formulas to audio-transcription exist in isolation, their integration has been barely tested and, more importantly, the quality of the resulting experience has not been measured. The project Read-Aloud Maths aims to investigate challenges and solutions for all realistic learning situations where written texts and formulas are “read-aloud” by means of speech synthesis.

More precisely we want to answer:

Q1: How can the accessibility of mathematical content in digital form be assessed from the perspective of real users employing standard and advanced assistive technologies (at IU and beyond)?
Q2: Which types of errors and ambiguities most significantly affect usability and learning outcomes, and how can they be systematically detected and mitigated in the authoring workflow?
Q3: How do different learner groups – distinguished by disability, learning context, and user preference – interact with and benefit from mathematical speech output, and what are their specific requirements for language, interactivity, and reliability?

To answer these questions, this incubator will select representative course content and enrich it under the eyes of professional mathematicians, who will ensure proper semantics. It will experimentally measure learning processes using spoken mathematical content. Alongside it will generate a ground truth corpus of expressions and their audio speech, in English and German. The enrichment will be so complete that one can obtain a realistic representation of the future conversion processes. Both the tools for the enrichment and the tools for reading-aloud will include widespread accessibility tools (e.g. web-browsers, rule-based accessibility tools) as well as state-of-the-art large language models’ pipelines to compare and to convert content.

Dauer des Projekts

04/2026 – 03/2028

Weitere Infos

Prof. Dr.-Ing. Paul Libbrecht, Paul.libbrecht@iu.org
Prof. Dr. Paul Libbrecht, Professor of Computer Science and Data Science since 2020: Originally a mathematician, he became a computer scientist and worked in research at DFKI, Universities in Germany and educational technology companies in USA and France. His research interests include the authoring and learning processes in mathematics using computers, especially on the worldwide web. His publication records include international conferences, journals and workshops and he has been reviewing for many conferences and editing, e.g., for Frontiers of AI. He is an invited expert for the W3C Math Working group since 2009 and has been contributing to open-source projects such as XWiki, Apache Commons or MathCAT. In the Read-Aloud Maths incubator, he will coordinate the project and lead T0 (preparation) and T5 (dissemination).
Prof. Dr. rer. nat. Robert Graf,
Prof. Dr. Robert Graf, Professor of Applied Mathematics: Since joining IU in 2021, Robert has acted as a module director and tutor for a variety of courses in the areas of mathematics, statistics, and computer science, both in German and English language. Having worked extensively with TEAQ, he is experienced in the underlying XML format (in particular with MathML), and he has a good overview of typical challenges in the typesetting of mathematical formulas in IU’s course materials. As part of the incubator, Robert will lead workstream T1, which will implement fundamental adjustments to selected content pieces to make them ready for meaningful speech output, as well as workstream T4, which will further refine the content for a high-quality output.
Prof. Dr. rer. nat. Nazli Andjic,
Prof. Dr. Nazli Andjic, Professor of Statistics and Quantitative Methods at IU with extensive teaching experience in mathematics and statistics. She is teaching several courses in mathematics and statistics at the IU, for multiple levels of proficiency. Her strong applied focus, working intensively with real-world data such as done in her role as data-scientist at the AOK Bundesverband, will be precious for leading the workstream T3 (experimental usage). Her expertise in experimental learning designs and pedagogical evaluation will ensure the project’s impact on student learning.
Prof. Dr. Tim Schlippe,
Prof. Dr. Tim Schlippe, Professor of Artificial Intelligent at IU since 2020. After PhD at the Karlsruhe Institute of Technology and a MSc Thesis at Carnegie Mellon University, he worked at Across Systems GmbH and is now CEO of Silicon Surfer where AI -products are developed for visualizing information and emotion from the voice in subtitles and captions. His in depth knowledge of AI, machine learning, natural language processing and multilingual speech technologies will be precious for the project where he will lead the workstream T2 (Advanced Evaluations). He brings the expertise in the formula2text corpus and experience with large language models and visualizations.