Using NLG for speech synthesis of mathematical sentences

Alessandro Mazzei, Michele Monticone, Cristian Bernareggi

Abstract
People with sight impairments can access to a mathematical expression by using its LaTeX source. However, this mechanisms have several drawbacks: (1) it assumes the knowledge of the LaTeX, (2) it is slow, since LaTeX is verbose and (3) it is error-prone since LATEX is a typographical language. In this paper we study the design of a natural language generation system for producing a mathematical sentence, i.e. a natural language sentence expressing the semantics of a mathematical expression. Moreover, we describe the main results of a first human based evaluation experiment of the system for Italian language.
Anthology ID:
W19-8658
Volume:
Proceedings of the 12th International Conference on Natural Language Generation
Month:
October–November
Year:
2019
Address:
Tokyo, Japan
Editors:
Kees van Deemter, Chenghua Lin, Hiroya Takamura
Venue:
INLG
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
463–472
Language:
URL:
https://aclanthology.org/W19-8658
DOI:
10.18653/v1/W19-8658
Bibkey:
Cite (ACL):
Alessandro Mazzei, Michele Monticone, and Cristian Bernareggi. 2019. Using NLG for speech synthesis of mathematical sentences. In Proceedings of the 12th International Conference on Natural Language Generation, pages 463–472, Tokyo, Japan. Association for Computational Linguistics.
Cite (Informal):
Using NLG for speech synthesis of mathematical sentences (Mazzei et al., INLG 2019)
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PDF:
https://preview.aclanthology.org/ml4al-ingestion/W19-8658.pdf
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