A Chart-Parsing Algorithm for Efficient Semantic Analysis

A Chart-Parsing Algorithm for Efficient Semantic Analysis Pascal Vaillant ENST/TSI 46, rue Barrault, 75634 Paris cedex 13, France E-mail: vaillant@tsi.enst.fr Abstract In some contexts, well-formed natural language cannot be expected as input to information or communication systems. In these contexts, the use of grammar-independent input (sequences of uninflected semantic units like e.g. language- independent icons) can be an answer to the users’ needs. However, this requires that an intelligent sys- tem should be able to interpret this input with rea- sonable accuracy and in reasonable time. Here we propose a method allowing a purely semantic-based analysis of sequences of semantic units. It uses an algorithm inspired by the idea of “chart pars- ing” known in Natural Language Processing, which stores intermediate parsing results in order to bring the calculation time down. Introduction As the mass of international communication and ex- change increases, icons as a mean to cross the lan- guage barriers have come through in some specific contexts of use, where language independent sym- bols are needed (e.g. on some machine command buttons). The renewed interest in iconic communi- cation has given rise to important works in the field of Design (Aicher and Krampen, 1996; Dreyfuss, 1984; Ota, 1993), on reference books on the history and development of the matter (Frutiger, 1991; Li- ungman, 1995; Sassoon and Gaur, 1997), as well as newer studies in the fields of Human-Computer Interaction and Digital Media (Yazdani and Barker, 2000) or Semiotics (Vaillant, 1999). We are here particularly interested in the field of Information Technology. Icons are now used in nearly all possible areas of human computer in- teraction, even office software or operating sys- tems. However, there are contexts where richer information has to be managed, for instance: Al- ternative & Augmentative Communication systems designed for the needs of speech or language im- paired people, to help them communicate (with icon languages like Minspeak, Bliss, Commun-I-Mage); Second Language Learning systems where learn- ers have a desire to communicate by themselves, but do not master the structures of the target lan- guage yet; Cross-Language Information Retrieval systems, with a visual symbolic input. In these contexts, the use of icons has many ad- vantages: it makes no assumption about the lan- guage competences of the users, allowing impaired users, or users from a different linguistic back- ground (which may not include a good command of one of the major languages involved in research on natural language processing), to access the systems; it may trigger a communication-motivated, implicit learning process, which helps the users to gradu- ally improve their level of literacy in the target lan- guage. However, icons suffer from a lack of expres- sive power to convey ideas, namely, the expression of abstract relations between concepts still requires the use of linguistic communication. An approach to tackle this limitation is to try to “analyse” sequences of icons like natural language sentences are parsed, for example. However, icons do not give grammatical information as clues to au- tomatic parsers. Hence, we have defined …

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