Papers with finite state transducer

5 papers
A Corpus and Method for Chinese Named Entity Recognition in Manufacturing (2024.lrec-main)

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Challenge: Existing resources and techniques for named entity recognition (NER) for manufacturing-specific named entities are limited.
Approach: They propose a corpus of Chinese manufacturing specifications, named MS-NERC, with 4,424 sentences and 16,383 entities.
Outcome: The proposed model outperforms neural methods in few-shot and rich-resource domains.
Neural Finite-State Transducers: Beyond Rational Relations (N19-1)

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Challenge: a finite state transducer defines joint and conditional probability distributions over strings . a weighted finite-state transducers can only model certain functions, known as the rational relations .
Approach: They propose a family of string transduction models defining joint and conditional probability distributions over pairs of strings.
Outcome: The proposed models are more powerful than previous finite-state models with neural features.
An Expanded Finite-State Transducer for Tsuut’ina Verbs (2022.lrec-1)

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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.
Bootstrapping Techniques for Polysynthetic Morphological Analysis (2020.acl-main)

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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.
Criteria for Useful Automatic Romanization in South Asian Languages (2022.lrec-1)

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Challenge: a number of possible criteria for systems that transliterate South Asian languages are considered . romanization is the special case where the target script is the Latin script.
Approach: They propose a set of criteria for systems that transliterate South Asian languages . criteria include fidelity to human linguistic behavior, processing utility for people, invertibility . they then propose several algorithms that address different criteria .
Outcome: The proposed algorithms address linguistic considerations in the context of Brahmic scripts and languages that use them, such as Hindi and Malayalam.

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