| ROA: | 262 |
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| Title: | Robust Interpretive Parsing in Metrical Stress Theory |
| Authors: | Bruce Tesar |
| Comment: | |
| Length: | 15 |
| Abstract: | Robust Interpretive Parsing in Metrical Stress Theory Bruce Tesar Rutgers University Most computational work to date within Optimality Theory (Prince & Smolensky 1993) has focused on generation, the mapping from an underlying form to its full structural description (Eisner (1997), Ellison (1995), Frank & Satta (to appear), Tesar (1995)). While that is a natural starting place, it is not the only function of interest related to an OT grammar. Language comprehension involves the interpretation of overt forms, forms consisting of the auditory information directly available to a listener. The function is not the inverse of generation, but the mapping from an overt form to its full structural description. The process of computing this latter function is here called interpretive parsing. This paper presents an efficient algorithm for the interpretive parsing of forms using an optimality theoretic system of metrical stress grammars. The system has 8 freely rankable constraints, and can account for a wide variety of metrical phenomena. The full structural descriptions include foot structure and the assignment of stress levels to the syllables, while the overt forms include the syllables and their stress levels, but not the foot structure. Overt forms are inherently ambiguous; the same pattern of stress levels is consistent with multiple foot structures. Interpretive parsing must recover the correct foot structure from the overt form, using the constraint ranking of the grammar. The algorithm is based upon the dynamic programming approach of Tesar, but includes non-trivial extensions to efficiently deal with the non-localities of metrical structure. Interpretive parsing poses an interesting issue that does not arise in generation: the issue of dealing with overt forms that are ungramma- tical according to the learner's current grammar. By definition, an optimality theoretic grammar assigns a description to every possible input. But there can be overt forms which do not correspond to any optimal structural description of a grammar. The approach presented in this paper assigns the best possible interpretation to an overt form, whether it is grammatical or not. Thus, the procedure is called robust interpretive parsing. Robust interpretive parsing has great significance for language learning. A learner in the process of learning their native language does not yet have the correct grammar, and thus needs to be able to interpret the form even when it is ungrammatical with respect to their current grammar. Robust interpretive parsing allows a child to use what they have already learned to estimate a best interpretation of overt forms, which they can then use to perform further learning. Significant learning results, reported elsewhere, have already been obtained using this approach to learning. This paper will appear in the Proceedings of the WCCFL XVII. |
| Type: | Paper/tech report |
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| Article: | Part 1 Part 2 Part 3 Part 4 Part 5 Part 6 Part 7 Part 8 Part 9 Part 10 Part 11 Part 12 Part 13 |