Papers Morphological Inflection
“Morphological Inflection” 태그가 달린 논문 135편 · 필터 해제
Improving Low-Resource Morphological Inflection via Self-Supervised Objectives
Self-supervised objectives have driven major advances in NLP by leveraging large-scale unlabeled data, but such resources are scarce for many of the world's languages. Surprisingly, they have not been explored much for c…
DecoderLanguage ModelingLanguage ModellingMasked Language Modeling+1Probing Subphonemes in Morphology Models
Transformers have achieved state-of-the-art performance in morphological inflection tasks, yet their ability to generalize across languages and morphological rules remains limited. One possible explanation for this behav…
Morphological InflectionCan a Neural Model Guide Fieldwork? A Case Study on Morphological Data Collection
Linguistic fieldwork is an important component in language documentation and preservation. However, it is a long, exhaustive, and time-consuming process. This paper presents a novel model that guides a linguist during th…
DiversityMorphological InflectionOOVs in the Spotlight: How to Inflect them?
We focus on morphological inflection in out-of-vocabulary (OOV) conditions, an under-researched subtask in which state-of-the-art systems usually are less effective. We developed three systems: a retrograde model and two…
LEMMAMorphological InflectionExploring Linguistic Probes for Morphological Generalization
Modern work on the cross-linguistic computational modeling of morphological inflection has typically employed language-independent data splitting algorithms. In this paper, we supplement that approach with language-speci…
Morphological InflectionMorphological Inflection with Phonological Features
Recent years have brought great advances into solving morphological tasks, mostly due to powerful neural models applied to various tasks as (re)inflection and analysis. Yet, such morphological tasks cannot be considered …
Morphological InflectionAn Investigation of Noise in Morphological Inflection
With a growing focus on morphological inflection systems for languages where high-quality data is scarce, training data noise is a serious but so far largely ignored concern. We aim at closing this gap by investigating t…
Language ModelingLanguage ModellingMasked Language ModelingMorphological InflectionMorphological Inflection: A Reality Check
Morphological inflection is a popular task in sub-word NLP with both practical and cognitive applications. For years now, state-of-the-art systems have reported high, but also highly variable, performance across data set…
Morphological InflectionUnderstanding Compositional Data Augmentation in Typologically Diverse Morphological Inflection
Data augmentation techniques are widely used in low-resource automatic morphological inflection to overcome data sparsity. However, the full implications of these techniques remain poorly understood. In this study, we ai…
AttributeData AugmentationMorphological InflectionA Framework for Bidirectional Decoding: Case Study in Morphological Inflection
Transformer-based encoder-decoder models that generate outputs in a left-to-right fashion have become standard for sequence-to-sequence tasks. In this paper, we propose a framework for decoding that produces sequences fr…
DecoderLEMMAMorphological InflectionAutoregressive Modeling with Lookahead Attention
To predict the next token, autoregressive models ordinarily examine the past. Could they also benefit from also examining hypothetical futures? We consider a novel Transformer-based autoregressive architecture that estim…
Morphological InflectionAn Extended Sequence Tagging Vocabulary for Grammatical Error Correction
We extend a current sequence-tagging approach to Grammatical Error Correction (GEC) by introducing specialised tags for spelling correction and morphological inflection using the SymSpell and LemmInflect algorithms. Our …
Grammatical Error CorrectionMorphological InflectionSpelling CorrectionModeling the Graphotactics of Low-Resource Languages Using Sequential GANs
Generative Adversarial Networks (GANs) have been shown to aid in the creation of artificial data in situations where large amounts of real data are difficult to come by. This issue is especially salient in the computatio…
Morphological InflectionEeny, meeny, miny, moe. How to choose data for morphological inflection
Data scarcity is a widespread problem in numerous natural language processing (NLP) tasks for low-resource languages. Within morphology, the labour-intensive work of tagging/glossing data is a serious bottleneck for both…
Active LearningMorphological InflectionA Comprehensive Comparison of Neural Networks as Cognitive Models of Inflection
Neural networks have long been at the center of a debate around the cognitive mechanism by which humans process inflectional morphology. This debate has gravitated into NLP by way of the question: Are neural networks a f…
Morphological InflectionSIGMORPHON–UniMorph 2022 Shared Task 0: Modeling Inflection in Language Acquisition
This year’s iteration of the SIGMORPHONUniMorph shared task on “human-like” morphological inflection generation focuses on generalization and errors in language acquisition. Systems are trained on data sets extracted fro…
Language AcquisitionMorphological InflectionSIGMORPHON–UniMorph 2022 Shared Task 0: Generalization and Typologically Diverse Morphological Inflection
The 2022 SIGMORPHON–UniMorph shared task on large scale morphological inflection generation included a wide range of typologically diverse languages: 33 languages from 11 top-level language families: Arabic (Modern Stand…
Morphological InflectionSIGMORPHON 2022 Task 0 Submission Description: Modelling Morphological Inflection with Data-Driven and Rule-Based Approaches
This paper describes our participation in the 2022 SIGMORPHON-UniMorph Shared Task on Typologically Diverse and AcquisitionInspired Morphological Inflection Generation. We present two approaches: one being a modification…
DecoderMorphological InflectionCLUZH at SIGMORPHON 2022 Shared Tasks on Morpheme Segmentation and Inflection Generation
This paper describes the submissions of the team of the Department of Computational Linguistics, University of Zurich, to the SIGMORPHON 2022 Shared Tasks on Morpheme Segmentation and Inflection Generation. Our submissio…
GPUMorpheme SegmentaitonMorphological InflectionSegmentation+1Generalizing Morphological Inflection Systems to Unseen Lemmas
This paper presents experiments on morphological inflection using data from the SIGMORPHON-UniMorph 2022 Shared Task 0: Generalization and Typologically Diverse Morphological Inflection. We present a transformer inflecti…
HallucinationLEMMAMorphological Inflection