Search Results for author:
Found 47 papers, 6 papers with code
Penalizing Divergence: Multi-Parallel Translation for Low-Resource Languages of North America
Experiments on very low-resourced Indigenous North American languages show that an initially deficient multilingual translator can improve by 4. 9 BLEU through mBART pre-training, and 5. 5 BLEU points with the strategic addition of monolingual data, and that a divergence penalty leads to further increases of 0. 4 BLEU.
Morphological Processing of Low-Resource Languages: Where We Are and What’s Next
Automatic morphological processing can aid downstream natural language processing applications, especially for low-resource languages, and assist language documentation efforts for endangered languages.
An Inflectional Database for Gitksan
We use Gitksan data in interlinear glossed format, stemming from language documentation efforts, to build a database of partial inflection tables.
Generalizing 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.
Dim Wihl Gat Tun: The Case for Linguistic Expertise in NLP for Under-Documented Languages
With this paper, we make the case that IGT data can be leveraged successfully provided that target language expertise is available.
SIGMORPHON 2021 Shared Task on Morphological Reinflection: Generalization Across Languages
This year's iteration of the SIGMORPHON Shared Task on morphological reinflection focuses on typological diversity and cross-lingual variation of morphosyntactic features.
An FST morphological analyzer for the Gitksan language
This paper presents a finite-state morphological analyzer for the Gitksan language.
Linguistic Knowledge in Multilingual Grapheme-to-Phoneme Conversion
This paper documents the UBC Linguistics team’s approach to the SIGMORPHON 2021 Grapheme-to-Phoneme Shared Task, concentrating on the low-resource setting.
Unsupervised Paradigm Clustering Using Transformation Rules
Secondly, we experiment with more general rules which can apply transformations inside the input strings in addition to prefix and suffix transformations.
Findings of the SIGMORPHON 2021 Shared Task on Unsupervised Morphological Paradigm Clustering
We describe the second SIGMORPHON shared task on unsupervised morphology: the goal of the SIGMORPHON 2021 Shared Task on Unsupervised Morphological Paradigm Clustering is to cluster word types from a raw text corpus into paradigms.
Multiple Sources are Better Than One: Incorporating External Knowledge in Low-Resource Glossing
In this paper, we address the data scarcity problem in automatic data-driven glossing for low-resource languages by coordinating multiple sources of linguistic expertise.
Embedded Translations for Low-resource Automated Glossing
Aided by these enhancements, our model demonstrates an average improvement of 3. 97\%-points over the previous state of the art on datasets from the SIGMORPHON 2023 Shared Task on Interlinear Glossing.
Neural Machine Translation Data Generation and Augmentation using ChatGPT
Neural models have revolutionized the field of machine translation, but creating parallel corpora is expensive and time-consuming.
An Investigation of Noise in Morphological Inflection
We aim at closing this gap by investigating the types of noise encountered within a pipeline for truly unsupervised morphological paradigm completion and its impact on morphological inflection systems: First, we propose an error taxonomy and annotation pipeline for inflection training data.
UniMorph 4.0: Universal Morphology
The project comprises two major thrusts: a language-independent feature schema for rich morphological annotation and a type-level resource of annotated data in diverse languages realizing that schema.
Dim Wihl Gat Tun: The Case for Linguistic Expertise in NLP for Underdocumented Languages
With this paper, we make the case that IGT data can be leveraged successfully provided that target language expertise is available.
Morphological Processing of Low-Resource Languages: Where We Are and What's Next
Automatic morphological processing can aid downstream natural language processing applications, especially for low-resource languages, and assist language documentation efforts for endangered languages.
Do RNN States Encode Abstract Phonological Alternations?
Sequence-to-sequence models have delivered impressive results in word formation tasks such as morphological inflection, often learning to model subtle morphophonological details with limited training data.
Do RNN States Encode Abstract Phonological Processes?
Sequence-to-sequence models have delivered impressive results in word formation tasks such as morphological inflection, often learning to model subtle morphophonological details with limited training data.
Noise Isn't Always Negative: Countering Exposure Bias in Sequence-to-Sequence Inflection Models
Morphological inflection, like many sequence-to-sequence tasks, sees great performance from recurrent neural architectures when data is plentiful, but performance falls off sharply in lower-data settings.
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection
Systems were developed using data from 45 languages and just 5 language families, fine-tuned with data from an additional 45 languages and 10 language families (13 in total), and evaluated on all 90 languages.
The SIGMORPHON 2020 Shared Task on Unsupervised Morphological Paradigm Completion
In this paper, we describe the findings of the SIGMORPHON 2020 shared task on unsupervised morphological paradigm completion (SIGMORPHON 2020 Task 2), a novel task in the field of inflectional morphology.
The Johns Hopkins University Bible Corpus: 1600+ Tongues for Typological Exploration
The corpus consists of over 4000 unique translations of the Christian Bible and counting.
Cross-Linguistic Syntactic Evaluation of Word Prediction Models
On other constructions, agreement accuracy was generally higher in languages with richer morphology.
JHUBC's Submission to LT4HALA EvaLatin 2020
We describe the JHUBC submission to the EvaLatin Shared task on lemmatization and part-of-speech tagging for Latin.
Fine-grained Morphosyntactic Analysis and Generation Tools for More Than One Thousand Languages
Exploiting the broad translation of the Bible into the world{'}s languages, we train and distribute morphosyntactic tools for approximately one thousand languages, vastly outstripping previous distributions of tools devoted to the processing of inflectional morphology.
Multilingual Dictionary Based Construction of Core Vocabulary
We propose a new functional definition and construction method for core vocabulary sets for multiple applications based on the relative coverage of a target concept in thousands of bilingual dictionaries.
An Analysis of Massively Multilingual Neural Machine Translation for Low-Resource Languages
We find that best practices in this domain are highly language-specific: adding more languages to a training set is often better, but too many harms performance{---}the best number depends on the source language.
Low Resource Neural Machine Translation
Low-Resource Neural Machine Translation
+1
UniMorph 3.0: Universal Morphology
The project comprises two major thrusts: a language-independent feature schema for rich morphological annotation and a type-level resource of annotated data in diverse languages realizing that schema.
Induced Inflection-Set Keyword Search in Speech
We investigate the problem of searching for a lexeme-set in speech by searching for its inflectional variants.
The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection
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 contextual lemmatization and morphosyntactic description in 66 languages.
Learning Morphosyntactic Analyzers from the Bible via Iterative Annotation Projection across 26 Languages
A large percentage of computational tools are concentrated in a very small subset of the planet{'}s languages.
The CoNLL--SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection
Apart from extending the number of languages involved in earlier supervised tasks of generating inflected forms, this year the shared task also featured a new second task which asked participants to inflect words in sentential context, similar to a cloze task.
String Transduction with Target Language Models and Insertion Handling
Many character-level tasks can be framed as sequence-to-sequence transduction, where the target is a word from a natural language.
Morphological Analysis without Expert Annotation
The task of morphological analysis is to produce a complete list of lemma+tag analyses for a given word-form.
Bootstrapping Unsupervised Bilingual Lexicon Induction
The task of unsupervised lexicon induction is to find translation pairs across monolingual corpora.
