Improving Low-Resource Morphological Learning with Intermediate Forms from Finite State Transducers
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Evaluating Unsupervised Approaches to Morphological Segmentation for Wolastoqey
Finite-state approaches to morphological analysis have been shown to improve the performance of natural language processing systems for polysynthetic languages, in-which words are generally composed of many morphemes, fo…
Language ModellingMorphological AnalysisTools for supporting language learning for Sakha
This paper presents an overview of the available linguistic resources for the Sakha language, and presents new tools for supporting language learning for Sakha. The essential resources include a morphological analyzer, d…
BabyFST - Towards a Finite-State Based Computational Model of Ancient Babylonian
Akkadian is a fairly well resourced extinct language that does not yet have a comprehensive morphological analyzer available. In this paper we describe a general finite-state based morphological model for Babylonian, a s…
LemmatizationPOSPOS TaggingImproved Finite-State Morphological Analysis for St. Lawrence Island Yupik Using Paradigm Function Morphology
St. Lawrence Island Yupik is an endangered polysynthetic language of the Bering Strait region. While conducting linguistic fieldwork between 2016 and 2019, we observed substantial support within the Yupik community for l…
Morphological AnalysisAn Unsupervised Method for Weighting Finite-state Morphological Analyzers
Morphological analysis is one of the tasks that have been studied for years. Different techniques have been used to develop models for performing morphological analysis. Models based on finite state transducers have prov…
Morphological Analysis