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International Conference on Implementation and Application of Automata

CIAA 2019: Implementation and Application of Automata pp 133–145Cite as

Composition Closure of Linear Weighted Extended Top-Down Tree Transducers

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11601))

Abstract

Linear weighted extended top-down tree transducers with regular look-ahead and with weights from a semiring are formal models that are used in syntax-based statistical machine translation. The composition hierarchies of some restricted versions of such weighted tree transducers (also without regular look-ahead) are considered. In particular, combinations of the restrictions of \(\varepsilon \)-freeness (all rules consume input), nondeletion, and strictness (all rules produce output) are considered. The composition hierarchy is shown to be finite for all but one \(\varepsilon \)-free variant of these weighted transducers over any commutative semiring.

Z. Fülöp—Supported by NKFI grant K 108 448 and by grant 20391-3/2018/FEKUSTRAT of the Ministry of Human Capacities, Hungary.

A. Maletti—Partially supported by the DFG research training group 1763 ‘QuantLA’.

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Authors and Affiliations

  1. Department of Foundations of Computer Science, University of Szeged, Árpád tér 2, Szeged, 6720, Hungary

    Zoltán Fülöp

  2. Department of Mathematics and Computer Science, Universität Leipzig, PO Box 100 920, 04009, Leipzig, Germany

    Andreas Maletti

Authors
  1. Zoltán Fülöp
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  2. Andreas Maletti
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Correspondence to Andreas Maletti .

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Editors and Affiliations

  1. Slovak Academy of Sciences, Košice, Slovakia

    Michal Hospodár

  2. Slovak Academy of Sciences, Košice, Slovakia

    Galina Jirásková

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Fülöp, Z., Maletti, A. (2019). Composition Closure of Linear Weighted Extended Top-Down Tree Transducers. In: Hospodár, M., Jirásková, G. (eds) Implementation and Application of Automata. CIAA 2019. Lecture Notes in Computer Science(), vol 11601. Springer, Cham. https://doi.org/10.1007/978-3-030-23679-3_11

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  • DOI: https://doi.org/10.1007/978-3-030-23679-3_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-23678-6

  • Online ISBN: 978-3-030-23679-3

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