Jeffrey Heinz


2021

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Finite-state Model of Shupamem Reduplication
Magdalena Markowska | Jeffrey Heinz | Owen Rambow
Proceedings of the 18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology

Shupamem, a language of Western Cameroon, is a tonal language which also exhibits the morpho-phonological process of full reduplication. This creates two challenges for finite-state model of its morpho-syntax and morphophonology: how to manage the full reduplication and the autosegmental nature of lexical tone. Dolatian and Heinz (2020) explain how 2-way finite-state transducers can model full reduplication without an exponential increase in states, and finite-state transducers with multiple tapes have been used to model autosegmental tiers, including tone (Wiebe, 1992; Dolatian and Rawski, 2020a). Here we synthesize 2-way finite-state transducers and multitape transducers, resulting in a finite-state formalism that subsumes both, to account for the full reduplicative processes in Shupamem which also affect tone.

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Strong generative capacity of morphological processes
Hossep Dolatian | Jonathan Rawski | Jeffrey Heinz
Proceedings of the Society for Computation in Linguistics 2021

2019

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RedTyp: A Database of Reduplication with Computational Models
Hossep Dolatian | Jeffrey Heinz
Proceedings of the Society for Computation in Linguistics (SCiL) 2019

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Proceedings of the Workshop on Deep Learning and Formal Languages: Building Bridges
Jason Eisner | Matthias Gallé | Jeffrey Heinz | Ariadna Quattoni | Guillaume Rabusseau
Proceedings of the Workshop on Deep Learning and Formal Languages: Building Bridges

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The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection
Arya D. McCarthy | Ekaterina Vylomova | Shijie Wu | Chaitanya Malaviya | Lawrence Wolf-Sonkin | Garrett Nicolai | Christo Kirov | Miikka Silfverberg | Sabrina J. Mielke | Jeffrey Heinz | Ryan Cotterell | Mans Hulden
Proceedings of the 16th Workshop on Computational Research in Phonetics, Phonology, and Morphology

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. The first task evolves past years’ inflection tasks by examining transfer of morphological inflection knowledge from a high-resource language to a low-resource language. This year also presents a new second challenge on lemmatization and morphological feature analysis in context. All submissions featured a neural component and built on either this year’s strong baselines or highly ranked systems from previous years’ shared tasks. Every participating team improved in accuracy over the baselines for the inflection task (though not Levenshtein distance), and every team in the contextual analysis task improved on both state-of-the-art neural and non-neural baselines.

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Learning with Partially Ordered Representations
Jane Chandlee | Remi Eyraud | Jeffrey Heinz | Adam Jardine | Jonathan Rawski
Proceedings of the 16th Meeting on the Mathematics of Language

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Maximum Likelihood Estimation of Factored Regular Deterministic Stochastic Languages
Chihiro Shibata | Jeffrey Heinz
Proceedings of the 16th Meeting on the Mathematics of Language

2018

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Modeling Reduplication with 2-way Finite-State Transducers
Hossep Dolatian | Jeffrey Heinz
Proceedings of the Fifteenth Workshop on Computational Research in Phonetics, Phonology, and Morphology

This article describes a novel approach to the computational modeling of reduplication. Reduplication is a well-studied linguistic phenomenon. However, it is often treated as a stumbling block within finite-state treatments of morphology. Most finite-state implementations of computational morphology cannot adequately capture the productivity of unbounded copying in reduplication, nor can they adequately capture bounded copying. We show that an understudied type of finite-state machines, two-way finite-state transducers (2-way FSTs), captures virtually all reduplicative processes, including total reduplication. 2-way FSTs can model reduplicative typology in a way which is convenient, easy to design and debug in practice, and linguistically-motivated. By virtue of being finite-state, 2-way FSTs are likewise incorporable into existing finite-state systems and programs. A small but representative typology of reduplicative processes is described in this article, alongside their corresponding 2-way FST models.

2016

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Learning Tier-based Strictly 2-Local Languages
Adam Jardine | Jeffrey Heinz
Transactions of the Association for Computational Linguistics, Volume 4

The Tier-based Strictly 2-Local (TSL2) languages are a class of formal languages which have been shown to model long-distance phonotactic generalizations in natural language (Heinz et al., 2011). This paper introduces the Tier-based Strictly 2-Local Inference Algorithm (2TSLIA), the first nonenumerative learner for the TSL2 languages. We prove the 2TSLIA is guaranteed to converge in polynomial time on a data sample whose size is bounded by a constant.

2015

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Output Strictly Local Functions
Jane Chandlee | Rémi Eyraud | Jeffrey Heinz
Proceedings of the 14th Meeting on the Mathematics of Language (MoL 2015)

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A Concatenation Operation to Derive Autosegmental Graphs
Adam Jardine | Jeffrey Heinz
Proceedings of the 14th Meeting on the Mathematics of Language (MoL 2015)

2014

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Proceedings of the 2014 Joint Meeting of SIGMORPHON and SIGFSM
Özlem Çetinoğlu | Jeffrey Heinz | Andreas Maletti | Jason Riggle
Proceedings of the 2014 Joint Meeting of SIGMORPHON and SIGFSM

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Learning Strictly Local Subsequential Functions
Jane Chandlee | Rémi Eyraud | Jeffrey Heinz
Transactions of the Association for Computational Linguistics, Volume 2

We define two proper subclasses of subsequential functions based on the concept of Strict Locality (McNaughton and Papert, 1971; Rogers and Pullum, 2011; Rogers et al., 2013) for formal languages. They are called Input and Output Strictly Local (ISL and OSL). We provide an automata-theoretic characterization of the ISL class and theorems establishing how the classes are related to each other and to Strictly Local languages. We give evidence that local phonological and morphological processes belong to these classes. Finally we provide a learning algorithm which provably identifies the class of ISL functions in the limit from positive data in polynomial time and data. We demonstrate this learning result on appropriately synthesized artificial corpora. We leave a similar learning result for OSL functions for future work and suggest future directions for addressing non-local phonological processes.

2013

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Vowel Harmony and Subsequentiality
Jeffrey Heinz | Regine Lai
Proceedings of the 13th Meeting on the Mathematics of Language (MoL 13)

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Learning Subregular Classes of Languages with Factored Deterministic Automata
Jeffrey Heinz | James Rogers
Proceedings of the 13th Meeting on the Mathematics of Language (MoL 13)

2012

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Bounded copying is subsequential: Implications for metathesis and reduplication
Jane Chandlee | Jeffrey Heinz
Proceedings of the Twelfth Meeting of the Special Interest Group on Computational Morphology and Phonology

2011

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Tier-based Strictly Local Constraints for Phonology
Jeffrey Heinz | Chetan Rawal | Herbert G. Tanner
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

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Formal and Empirical Grammatical Inference
Jeffrey Heinz | Colin de la Higuera | Menno van Zannen
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts

2010

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Estimating Strictly Piecewise Distributions
Jeffrey Heinz | James Rogers
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics

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String Extension Learning
Jeffrey Heinz
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics

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Proceedings of the 11th Meeting of the ACL Special Interest Group on Computational Morphology and Phonology
Jeffrey Heinz | Lynne Cahill | Richard Wicentowski
Proceedings of the 11th Meeting of the ACL Special Interest Group on Computational Morphology and Phonology

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Maximum Likelihood Estimation of Feature-Based Distributions
Jeffrey Heinz | Cesar Koirala
Proceedings of the 11th Meeting of the ACL Special Interest Group on Computational Morphology and Phonology

2008

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Proceedings of the Tenth Meeting of ACL Special Interest Group on Computational Morphology and Phonology
Jason Eisner | Jeffrey Heinz
Proceedings of the Tenth Meeting of ACL Special Interest Group on Computational Morphology and Phonology

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Improving Word Segmentation by Simultaneously Learning Phonotactics
Daniel Blanchard | Jeffrey Heinz
CoNLL 2008: Proceedings of the Twelfth Conference on Computational Natural Language Learning

2006

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Learning Quantity Insensitive Stress Systems via Local Inference
Jeffrey Heinz
Proceedings of the Eighth Meeting of the ACL Special Interest Group on Computational Phonology and Morphology at HLT-NAACL 2006