Morphological Guesser as a Tool for Analyzing Field Data: Experiences with The Naukan Yupik Language

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Abstract

The paper presents the development and evaluation of two automated morphological analysis tools for Naukan Yupik (Yupik Eskimo Eskimo-Aleut): a dictionary-based morphological analyzer and a dictionary-free morphological guesser. Both tools are implemented with a two-stage approach to morphological modeling based on finite state automata. The study examines in detail the morphological features of Naukan Yupik that influence the development of automated analysis tools, including rich inflection and derivation, homonymy of morphological markers, and complex morphophonological processes. The effectiveness of both tools will be evaluated using a corpus of oral texts from 2022–2023. Particular attention is paid to the problem of overgeneration in the output of the morphological guesser and to ways of solving this problem through part-of-speech-based analysis separation. The results show that when working with field data, the use of a guesser can be more effective despite its known limitations.

About the authors

Elena Mikhailovna Budyanskaya

Institute of Linguistics of the RAS

Author for correspondence.
Email: budyanskaya.lena@gmail.com
Moscow, Russia

Anton Olegovich Buzanov

Institute of Linguistics of the RAS; High School of Economy

Email: anton.buzanov.00@gmail.com
Москва, Россия

Daria Olegovna Zhornik

Institute of Linguistics of the RAS

Email: daria.zhornik@yandex.ru
Moscow, Russia

Andrey Andreevich Pikhtin

Institute of Linguistics of the RAS; High School of Economy

Email: p_nafanyka@gmail.com
Moscow, Russia

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