Challenge: a transitive verb takes up to 1,740 unique features and is highly complex, with a morphological complexity of 80.3% . a finite-state approach has been used to build morphology and phonology resources for Nen, an underresourced language in Papua New Guinea.
Approach: They propose to use Finite-State methods to build a verbal morphological parser for an under-resourced Papuan language, Nen.
Outcome: The proposed model is half the size of the full decomposed model, while the 'Chunking' model is under half the scale of the decomposer, with an overall accuracy of 80.3%.

Similar Papers

An Expanded Finite-State Transducer for Tsuut’ina Verbs (2022.lrec-1)

Copied to clipboard

Challenge: a finite state transducer (FST) for the transitive verb system of Tsuut'ina (ISO 639-3: srs) is described for the Dene (Athabaskan) language spoken in Alberta, Canada.
Approach: They describe the expansion of a finite state transducer (FST) for the transitive verb system of Tsuut'ina (ISO 639-3: srs) Dene languages have unique templatic morphology, in which lexical, inflectional and derivational tiers are interlaced.
Outcome: The proposed model can handle a great range of common and rare argument structure types, including ditransitive and uniquely Dene object experiencer verbs.
Modeling Northern Haida Verb Morphology (L18-1)

Copied to clipboard

Challenge: a computational model of the verbal morphology of Northern Haida is being developed . the model is capable of handling complex affixation patterns and morphophonological alternations .
Approach: They propose a computational model of the verbal morphology of Northern Haida based on finite state machines with a focus on verbs.
Outcome: The proposed model can handle complex affixation patterns and morphophonological alternations in the native language.
A Morphological Analyzer for St. Lawrence Island / Central Siberian Yupik (L18-1)

Copied to clipboard

Challenge: St. Lawrence Island / Central Siberian Yupik is an endangered language . it exhibits pervasive agglutinative and polysynthetic properties .
Approach: They propose to implement a finite-state morphological analyzer for the endangered language . it cyclically interweaves morphology and phonology to account for the language's intricate morphophonological system.
Outcome: The proposed method cyclically interweaves morphology and phonology to account for the language's intricate morphophonological system.
An Unsupervised Method for Weighting Finite-state Morphological Analyzers (2020.lrec-1)

Copied to clipboard

Challenge: Morphological analysis is one of the tasks that have been studied for years.
Approach: They propose a method for weighting a morphological analyzer built using finite state transducers in order to disambiguate its results.
Outcome: The proposed model weights a word2vec model using untagged corpora and captures the semantic meaning of the words.
BabyFST - Towards a Finite-State Based Computational Model of Ancient Babylonian (2020.lrec-1)

Copied to clipboard

Challenge: morphological analyzer for Akkadian is not yet available for the extinct language . we present a general finite-state based model for Babylonian that can achieve a coverage of 97.3% and a recall of 93.7% on token level.
Approach: They propose a general finite-state based morphological model for Babylonian that can achieve a coverage of 97.3% and recall up to 93.7% on lemmatization and POS-tagging tasks.
Outcome: The proposed model can achieve coverage and recall of 97.3% on lemmatization and POS-tagging tasks on token level from a transcribed input.
Morphological Processing of Low-Resource Languages: Where We Are and What’s Next (2022.findings-acl)

Copied to clipboard

Challenge: Existing models for morphological processing are not suitable for low-resource languages, but they are still lacking in the field of computational morphology.
Approach: They propose to bridge two unsupervised models to understand a language’s morphology from raw text alone and propose to use them to improve their models.
Outcome: The proposed models perform reasonably, but there is room for improvement.
Parser combinators for Tigrinya and Oromo morphology (L18-1)

Copied to clipboard

Challenge: morphological parsers for two Afroasiatic languages are developed using a parser-combinator paradigm . the paradigm allows rapid development and ease of integration with other systems, but at a cost of non-optimal theoretical efficiency.
Approach: They propose a rule-based morphological parser paradigm for Tigrinya and Oromo languages . they use a parsers-combinator paradigm instead of a finite-state paradigm .
Outcome: The proposed paradigm allows rapid development and ease of integration with other systems, but at cost of non-optimal theoretical efficiency.
Finite-state morphological analysis for Gagauz (L18-1)

Copied to clipboard

Challenge: a finite-state approach to morphological analysis and generation of Gagauz is used . the model has a reasonable coverage over a range of freely-available corpora .
Approach: They propose a finite-state approach to morphological analysis and generation of Gagauz . they explicitly handle orthographic errors and variance, in addition to loan words .
Outcome: The proposed approach has a reasonable coverage over a range of freely-available corpora.
Bootstrapping Techniques for Polysynthetic Morphological Analysis (2020.acl-main)

Copied to clipboard

Challenge: Polysynthetic languages have exceptionally large and sparse vocabularies due to the number of morpheme slots and combinations in a word.
Approach: They propose linguistically-informed approaches for bootstrapping a neural morphological analyzer . they use a finite state transducer to train an encoder-decoder model .
Outcome: The proposed method improves on a polysynthetic language's model by "hallucinating" missing linguistic structure and resampling from a Zipf distribution to simulate a more natural distribution of morphemes.
Improved Finite-State Morphological Analysis for St. Lawrence Island Yupik Using Paradigm Function Morphology (2020.lrec-1)

Copied to clipboard

Challenge: St. Lawrence Island Yupik is an endangered polysynthetic language of the Bering Strait region . linguistic fieldwork observed substantial support within the Yupis for language revitalization .
Approach: They propose a finite-state morphological analyzer for the endangered Yupik language . they use the Paradigm Function Morphology theory of morphology to evaluate the results .
Outcome: The proposed morphological analyzer outperforms existing analyzers in accuracy and coverage rates across multiple datasets.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations