Unsupervised Extraction of Morphological Categories for Morphemes

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F24%3A10492904" target="_blank" >RIV/00216208:11320/24:10492904 - isvavai.cz</a>

Result on the web

<a href="https://link.springer.com/chapter/10.1007/978-3-031-70563-2_19" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-70563-2_19</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-70563-2_19" target="_blank" >10.1007/978-3-031-70563-2_19</a>

Result language

angličtina

Original language name

Unsupervised Extraction of Morphological Categories for Morphemes

Original language description

Words in natural language can be assigned to specific morphological categories. For example, the English word &apos;apples&apos; can be described using morphological labels like N;PL. The conditional probabilities on such word forms given the labels would reveal for English that the morpheme &apos;s&apos; is present almost always when the label N;PL appears. This indicates that the morphological properties of a word can be traced to its morphemes. We do not have any data resource that associates morphemes with morphological categories. We use UniMorph schema and datasets for universal morphological annotation as a source of morphological categories and morpheme segmentation. We align morphemes (or exponents) with the corresponding morphological categories based on the UniMorph schema for 12 languages. Given the multilingual nature of the task, we utilize unsupervised methods based on the INCREMENT P measure and IBM Models as we test out the effectiveness of alignment methods used in statistical machine translation. Our results in

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

27th International Conference on Text, Speech and Dialogue

ISBN

978-3-031-70563-2

ISSN

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e-ISSN

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Number of pages

13

Pages from-to

239-251

Publisher name

Springer

Place of publication

Cham, Switzerland

Event location

Brno, Czechia

Event date

Sep 11, 2024

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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