98 citations · 219 across the 12 of their papers we have counts for
16 papers
MUDIDI: A Two-Stage Framework for Multilingual Dictionary Digitization with Language Models
David Setiawan, Temuulen Khishigsuren, Milind Agarwal +3
Multilingual dictionaries are among the most valuable documentary resources for low-resource and endangered languages, yet many remain available only as scans. For many decades, th…
CommonMorph: Participatory Morphological Documentation Platform
Aso Mahmudi, Sina Ahmadi, Kemal Kurniawan +3
Collecting and annotating morphological data present significant challenges, requiring linguistic expertise, methodological rigour, and substantial resources. These barriers are pa…
Evaluating Subword Tokenization: Alien Subword Composition and OOV Generalization Challenge
Khuyagbaatar Batsuren, Ekaterina Vylomova, Verna Dankers +4
The popular subword tokenizers of current language models, such as Byte-Pair Encoding (BPE), are known not to respect morpheme boundaries, which affects the downstream performance…
UniMorph 4.0: Universal Morphology
Khuyagbaatar Batsuren, Omer Goldman, Salam Khalifa +93
The Universal Morphology (UniMorph) project is a collaborative effort providing broad-coverage instantiated normalized morphological inflection tables for hundreds of diverse world…
The SIGMORPHON 2022 Shared Task on Morpheme Segmentation
Khuyagbaatar Batsuren, Gábor Bella, Aryaman Arora +10
The SIGMORPHON 2022 shared task on morpheme segmentation challenged systems to decompose a word into a sequence of morphemes and covered most types of morphology: compounds, deriva…
SIGTYP 2021 Shared Task: Robust Spoken Language Identification
Elizabeth Salesky, Badr M. Abdullah, Sabrina J. Mielke +6
While language identification is a fundamental speech and language processing task, for many languages and language families it remains a challenging task. For many low-resource an…
SIGTYP 2020 Shared Task: Prediction of Typological Features
Johannes Bjerva, Elizabeth Salesky, Sabrina J. Mielke +6
Typological knowledge bases (KBs) such as WALS (Dryer and Haspelmath, 2013) contain information about linguistic properties of the world's languages. They have been shown to be use…
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection
Ekaterina Vylomova, Jennifer White, Elizabeth Salesky +25
A broad goal in natural language processing (NLP) is to develop a system that has the capacity to process any natural language. Most systems, however, are developed using data from…
The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection
Arya D. McCarthy, Ekaterina Vylomova, Shijie Wu +9
The SIGMORPHON 2019 shared task on cross-lingual transfer and contextual analysis in morphology examined transfer learning of inflection between 100 language pairs, as well as cont…
Contextualization of Morphological Inflection
Ekaterina Vylomova, Ryan Cotterell, Timothy Baldwin +2
Critical to natural language generation is the production of correctly inflected text. In this paper, we isolate the task of predicting a fully inflected sentence from its partiall…
UniMorph 2.0: Universal Morphology
Christo Kirov, Ryan Cotterell, John Sylak-Glassman +10
The Universal Morphology UniMorph project is a collaborative effort to improve how NLP handles complex morphology across the world's languages. The project releases annotated morph…
The CoNLL--SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection
Ryan Cotterell, Christo Kirov, John Sylak-Glassman +10
The CoNLL--SIGMORPHON 2018 shared task on supervised learning of morphological generation featured data sets from 103 typologically diverse languages. Apart from extending the numb…
Classifying Idiomatic and Literal Expressions Using Topic Models and Intensity of Emotions
Jing Peng, Anna Feldman, Ekaterina Vylomova
We describe an algorithm for automatic classification of idiomatic and literal expressions. Our starting point is that words in a given text segment, such as a paragraph, that are…
Paradigm Completion for Derivational Morphology
Ryan Cotterell, Ekaterina Vylomova, Huda Khayrallah +2
The generation of complex derived word forms has been an overlooked problem in NLP; we fill this gap by applying neural sequence-to-sequence models to the task. We overview the the…
CoNLL-SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection in 52 Languages
Ryan Cotterell, Christo Kirov, John Sylak-Glassman +8
The CoNLL-SIGMORPHON 2017 shared task on supervised morphological generation required systems to be trained and tested in each of 52 typologically diverse languages. In sub-task 1,…
Context-Aware Prediction of Derivational Word-forms
Ekaterina Vylomova, Ryan Cotterell, Timothy Baldwin +1
Derivational morphology is a fundamental and complex characteristic of language. In this paper we propose the new task of predicting the derivational form of a given base-form lemm…