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Rewrite rule gram mars with multitape automata

Hulden M.

Journal of Language Modelling

2017

Vol. 5, No. 1

107--130

The majority of computational implementations of phonological and morphophonological alternations rely on composing together individual finite state transducers that represent sound changes. Standard composition algorithms do not maintain the intermediate representations between the ultimate input and output forms. These intermedia te strings, however, can be very helpful for various tasks: enriching information (indispensable for models of historical linguistics), providing new avenues to debugging complex grammars, and offering explicit alignment information between morphemes, sound segments, and tags. This paper describes a multitape automaton approach to creating full models of sequences of sound alternation that implement phonological and morphological grammars. A model and a practical implementation of multitape automata is provided together with a multitape composition algorithm tailored to the representation used In this paper. Practical use cases of the approach are illustrated through two common examples: a phonological example of a complex rewrite rule grammar where multiple rules interact and a diachronic ex ample of modeling sound change over time.

ZeuScansion : A tool for scansion of English poetry

Agirrezabal M., Astigarraga A., Arrieta B., Hulden M.

Journal of Language Modelling

2016

Vol. 4, No. 1

3--28

We present a finite-state technology (FST) based system capable of performing metrical scansion of verse written in English. Scansion is the traditional task of analyzing the lines of a poem, marking the stressed and non-stressed elements and dividing the line into metrical feet. The system’s workflow is composed of several subtasks designer around finite-state machines that analyze verse by performing tokenization, part-of-speech tagging, stress placement, and stress-pattern prediction for unknown words. The scanner also classifies poems according to the predominant type of metrical foot found. We present a brief evaluation of the system using a gold standard corpus of humanscanned verse, on which a per-syllable accuracy of 86.78% is achieved. The program uses open-source components and is released under the GNU GPL license.