Accession Number : ADA276795


Title :   AMAR: A Computational Model of Autosegmental Phonology


Descriptive Note : Technical rept.


Corporate Author : MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB


Personal Author(s) : Albro, Daniel M


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a276795.pdf


Report Date : Oct 1993


Pagination or Media Count : 158


Abstract : This report describes a computational system with which phonologists may describe a natural language in terms of autosegmental phonology, currently the most advanced theory pertaining to the sound systems of human languages. This system allows linguists to easily test autosegmental hypotheses against a large corpus of data. The system was designed primarily with tonal systems in mind, but also provides support for tree or feature matrix representation of phonemes (as in the sound pattern of english), as well as syllable structures and other aspects of phonological theory. Under specification is allowed, and threes may be specified before, during, and after rule application. The association convention is automatically applied, and other principles such as the conjunctivity condition are supported. The method of representation was designed such that rules are designated in as close a fashion as possible to the existing conventions of autosegmental theory while adhering to a textual constraint for maximum portability.


Descriptors :   *COMPUTATIONAL LINGUISTICS , *NATURAL LANGUAGE , *PHONEMES , TEST AND EVALUATION , COMPUTERIZED SIMULATION , HUMANS , THEORY , STRUCTURES , LINGUISTICS , SYLLABLES , WORD ASSOCIATION , THESES , TREES , SOUND , PATTERNS , LANGUAGE , HYPOTHESES


Subject Categories : Linguistics
      Computer Programming and Software


Distribution Statement : APPROVED FOR PUBLIC RELEASE