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Part of book or chapter of book . 2024 . Peer-reviewed
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Author Intent: Eliminating Ambiguity in MathML

Authors: David Carlisle; Paul Libbrecht; Moritz Schubotz; Neil Soiffer;

Author Intent: Eliminating Ambiguity in MathML

Abstract

MathML has been successful in improving the accessibility of mathematical notation on the web. All major screen readers support MathML to generate speech, allow navigation of the math, and generate braille. A troublesome area remains: handling ambiguous notations such as \( \vert x\vert\). While it is possible to speak this syntactically, anecdotal evidence indicates most people prefer semantic speech such as ``absolute value of x'' or ``determinant of x'' instead of ``vertical bar x vertical bar'' when first hearing an expression. Several heuristics to infer semantics have improved speech, but ultimately, the author is the one who definitively knows how an expression is meant to be spoken. The W3C Math Working Group is in the process of allowing authors to convey their intent in MathML markup via an intent attribute. This paper describes that work.

This preprint has not undergone peer review or any post-submission improvements or corrections. The Version of Record of this contribution is published in Int. Conf. on Computers Helping People with Special Needs will be available online at TBD

Keywords

FOS: Computer and information sciences, Computer Science - Human-Computer Interaction, Computer Science - Digital Libraries, Digital Libraries (cs.DL), Human-Computer Interaction (cs.HC)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green