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Found 72 papers, 9 papers with code
Backtranslation in Neural Morphological Inflection
Backtranslation is a common technique for leveraging unlabeled data in low-resource scenarios in machine translation.
IGT2P: From Interlinear Glossed Texts to Paradigms
An intermediate step in the linguistic analysis of an under-documented language is to find and organize inflected forms that are attested in natural speech.
My Case, For an Adposition: Lexical Polysemy of Adpositions and Case Markers in Finnish and Latin
Adpositions and case markers contain a high degree of polysemy and participate in unique semantic role configurations.
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.
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.
Detecting Annotation Errors in Morphological Data with the Transformer
Annotation errors that stem from various sources are usually unavoidable when performing large-scale annotation of linguistic data.
Can we teach language models to gloss endangered languages?
We explore whether LLMs can be effective at the task of interlinear glossing with in-context learning, without any traditional training.
Historia Magistra Vitae: Dynamic Topic Modeling of Roman Literature using Neural Embeddings
Dynamic topic models have been proposed as a tool for historical analysis, but traditional approaches have had limited usefulness, being difficult to configure, interpret, and evaluate.
Do transformer models do phonology like a linguist?
Neural sequence-to-sequence models have been very successful at tasks in phonology and morphology that seemingly require a capacity for intricate linguistic generalisations.
Eeny, meeny, miny, moe. How to choose data for morphological inflection
In this paper, we explore four sampling strategies for the task of morphological inflection using a Transformer model: a pair of oracle experiments where data is chosen based on whether the model already can or cannot inflect the test forms correctly, as well as strategies based on high/low model confidence, entropy, as well as random selection.
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.
To POS Tag or Not to POS Tag: The Impact of POS Tags on Morphological Learning in Low-Resource Settings
However, the importance and usefulness of POS tags needs to be examined as NLP expands to low-resource languages because linguists who provide many annotated resources do not place priority on early identification and tagging of POS.
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.
Can a Transformer Pass the Wug Test? Tuning Copying Bias in Neural Morphological Inflection Models
Deep learning sequence models have been successfully applied to the task of morphological inflection.
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.
Analogy Models for Neural Word Inflection
Analogy is assumed to be the cognitive mechanism speakers resort to in order to inflect an unknown form of a lexeme based on knowledge of other words in a language.
Linguist vs. Machine: Rapid Development of Finite-State Morphological Grammars
Sequence-to-sequence models have proven to be highly successful in learning morphological inflection from examples as the series of SIGMORPHON/CoNLL shared tasks have shown.
Data Augmentation for Transformer-based G2P
The Transformer model has been shown to outperform other neural seq2seq models in several character-level tasks.
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.
Applying the Transformer to Character-level Transduction
The transformer has been shown to outperform recurrent neural network-based sequence-to-sequence models in various word-level NLP tasks.
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.
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.
UniMorph 2.0: Universal Morphology
The Universal Morphology UniMorph project is a collaborative effort to improve how NLP handles complex morphology across the world'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.
Marrying Universal Dependencies and Universal Morphology
The Universal Dependencies (UD) and Universal Morphology (UniMorph) projects each present schemata for annotating the morphosyntactic details of language.
Phonological Features for Morphological Inflection
Modeling morphological inflection is an important task in Natural Language Processing.
A Neural Morphological Analyzer for Arapaho Verbs Learned from a Finite State Transducer
We experiment with training an encoder-decoder neural model for mimicking the behavior of an existing hand-written finite-state morphological grammar for Arapaho verbs, a polysynthetic language with a highly complex verbal inflection system.
A Computational Model for the Linguistic Notion of Morphological Paradigm
In supervised learning of morphological patterns, the strategy of generalizing inflectional tables into more abstract paradigms through alignment of the longest common subsequence found in an inflection table has been proposed as an efficient method to deduce the inflectional behavior of unseen word forms.
Automatic Glossing in a Low-Resource Setting for Language Documentation
Morphological analysis of morphologically rich and low-resource languages is important to both descriptive linguistics and natural language processing.
On the Complexity and Typology of Inflectional Morphological Systems
We quantify the linguistic complexity of different languages' morphological systems.
The Computational Complexity of Distinctive Feature Minimization in Phonology
We find that the natural class decision problem is tractable (i. e. is in P), while the minimization problem is not; the decision version of the problem which determines whether a natural class can be defined with $k$ features or less is NP-complete.
On the Diachronic Stability of Irregularity in Inflectional Morphology
Many languages' inflectional morphological systems are replete with irregulars, i. e., words that do not seem to follow standard inflectional rules.
A Comparison of Feature-Based and Neural Scansion of Poetry
Automatic analysis of poetic rhythm is a challenging task that involves linguistics, literature, and computer science.
Weakly supervised learning of allomorphy
Most NLP resources that offer annotations at the word segment level provide morphological annotation that includes features indicating tense, aspect, modality, gender, case, and other inflectional information.
A phoneme clustering algorithm based on the obligatory contour principle
This paper explores a divisive hierarchical clustering algorithm based on the well-known Obligatory Contour Principle in phonology.
CoNLL-SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection in 52 Languages
In sub-task 2, systems were given a lemma and some of its specific inflected forms, and asked to complete the inflectional paradigm by predicting all of the remaining inflected forms.
Machine Learning for Metrical Analysis of English Poetry
In this work we tackle the challenge of identifying rhythmic patterns in poetry written in English.
How Regular is Japanese Loanword Adaptation? A Computational Study
The modifications that foreign loanwords undergo when adapted into Japanese have been the subject of much study in linguistics.
Deriving Morphological Analyzers from Example Inflections
This paper presents a semi-automatic method to derive morphological analyzers from a limited number of example inflections suitable for languages with alphabetic writing systems.
Morphological Analysis of Sahidic Coptic for Automatic Glossing
We report on the implementation of a morphological analyzer for the Sahidic dialect of Coptic, a now extinct Afro-Asiatic language.
Evaluating the Noisy Channel Model for the Normalization of Historical Texts: Basque, Spanish and Slovene
This paper presents a method for the normalization of historical texts using a combination of weighted finite-state transducers and language models.
ACTIV-ES: a comparable, cross-dialect corpus of `everyday' Spanish from Argentina, Mexico, and Spain
Corpus resources for Spanish have proved invaluable for a number of applications in a wide variety of fields.
Computer-aided morphology expansion for Old Swedish
In this paper we describe and evaluate a tool for paradigm induction and lexicon extraction that has been applied to Old Swedish.
Boosting statistical tagger accuracy with simple rule-based grammars
We report on several experiments on combining a rule-based tagger and a trigram tagger for Spanish.
