Convolutional neural networks for low-resource morpheme segmentation: baseline or state-of-the-art?
We apply convolutional neural networks to the task of shallow morpheme segmentation using low-resource datasets for 5 different languages. We show that both in fully supervised and semi-supervised settings our model beats previous state-of-the-art approaches. We argue that convolutional neural networks reflect local nature of morpheme segmentation better than other semi-supervised approaches.
Code (1)
Tasks
Morphological AnalysisSegmentationSimilar Papers 제목 키워드 기반
Using Contextual Information for Sentence-level Morpheme Segmentation
Recent advancements in morpheme segmentation primarily emphasize word-level segmentation, often neglecting the contextual relevance within the sentence. In this study, we redefine the morpheme segmentation task as a sequ…
SegmentationSentenceDeep Convolutional Networks for Supervised Morpheme Segmentation of Russian Language
The present paper addresses the task of morphological segmentation for Russian language. We show that deep convolutional neural networks solve this problem with F1-score of 98% over morpheme boundaries and beat existing …
SegmentationTAMS: Translation-Assisted Morphological Segmentation
Canonical morphological segmentation is the process of analyzing words into the standard (aka underlying) forms of their constituent morphemes. This is a core task in language documentation, and NLP systems have the pote…
SegmentationTranslationLearning Beyond Limits: Multitask Learning and Synthetic Data for Low-Resource Canonical Morpheme Segmentation
We introduce a transformer-based morpheme segmentation system that augments a low-resource training signal through multitask learning and LLM-generated synthetic data. Our framework jointly predicts morphological segment…
In-Context LearningSegmentationCross-lingual Word Segmentation and Morpheme Segmentation as Sequence Labelling
This paper presents our segmentation system developed for the MLP 2017 shared tasks on cross-lingual word segmentation and morpheme segmentation. We model both word and morpheme segmentation as character-level sequence l…
Segmentation