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Automated tableau generation using SPOT (Syntax Prosody in Optimality Theory)

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Published/Copyright: May 8, 2019
Linguistics Vanguard
From the journal Linguistics Vanguard Volume 5 Issue 1

Abstract

Much recent work on the syntax-prosody interface has been based in Optimality Theory. The typical analysis explicitly considers only a small number of candidates that could reasonably be expected to be optimal under some ranking, often without an explicit definition of GEN. Manually generating all the possible candidates, however, is prohibitively time-consuming for most input structures – the Too Many Candidates Problem. Existing software for OT uses regular expressions for automated generation and evaluation of candidates. However, regular expressions are too low in the Chomsky Hierarchy of language types to represent trees of arbitrary size, which are needed for syntax-prosody work. This paper presents a new computational tool for research in this area: Syntax-Prosody in Optimality Theory (SPOT). For a given input, SPOT generates all prosodic parses under certain assumptions about GEN, and evaluates them against all constraints in CON. This allows for in-depth comparison of the typological predictions made by different theories of GEN and CON at the syntax-prosody interface.

Keywords: syntax-prosody interface; Optimality Theory; Computational Tools in Phonology; prosody; OTWorkplace

Acknowledgements:

This material is based upon work supported by the National Science Foundation under Grant No. 1749368 (to Junko Ito and Armin Mester). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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Appendix A

The code for GEN can be found in candidategenerator.js. The function takes as its input a list of syntactic terminals (leaves) and a list of options (obeysNonrecursivity, obeysExhaustivity, obeysHeadedness).

  1. GEN(leaves) = gen(leaves) + phi_wrap(gen(leaves)

  1. gen(leaves)

    1. Base case: If there are 0 leaves in the input, return the list of candidates and terminate.

    2. Recursive case: If there is at least one leaf in the input, then:

      1. For i from 1 to the number of leaves in leaves,

        1. Case 1: The first i leaves in leaves attach directly to the parent.

          1. Let Leftside = the first i elements in leaves

          2. Let Rightsides = all the outputs of gen(the remaining leaves) that do not have w at their left edge (i.e., outputs that are either an empty tree, or a subtree with a phi boundary at its left edge)

          3. Combine Leftside with each element in Rightsides, and add the results to the candidate list

        2. Case 2: The first i leaves do not attach directly to the parent (they are wrapped in a phi).

          1. Leftsides = phi_wrap(gen(the first i elements in leaves))

          2. Rightsides = gen(the remaining elements in leaves)

          3. Cross Leftsides and Rightsides with each other. Add the results to the candidate list.

        3. Return the candidate list.

  1. phi_wrap(tree_list): Wrap each element of tree_list in a phi and return the resulting list. By calling GEN recursively, all the possible sub-trees are also incorporated into the candidate set.

Appendix B: Markedness constraint families implemented in SPOT

  1. Constraints on Binarity (Maximal and Minimal):

    1. Counting the number of branches a node has (Elfner 2012; Bellik and Kalivoda 2016):

      1. BinMin-branches

      2. BinMax-branches (categorical)

      3. BinMax-branches (gradient)

    2. Counting the number of leaves a node dominates (Ito and Mester 2007, to appear):

      1. BinMin-leaves

      2. BinMax-leaves (categorical)

      3. BinMax-leaves (gradient)

  1. Constraints on horizontal relationships:

    1. EqualSisters (Myrberg 2013)

      1. EqualSisters (adjacent)

      2. EqualSisters (pairwise)

      3. EqualSisters (first privilege)

    2. StrongStart (Selkirk 2011)

  1. Constraints on vertical relationships:

    1. Exhaustivity

    2. NonRecursivity

      1. Non-recursivity, assessed by dominated node

      2. Non-recursivity, assessed by non-overlapping leaves (Truckenbrodt 1999)

  1. Constraints on accent (developed for analyses of Japanese and Basque, Selkirk and Elordieta 2010, Ito and Mester 2013):

    1. Accent-As-Head

    2. NoLapse

Appendix C

The most important elements of the codebase are organized as follows (ordered by relevance):

  1. main/interface1.html: Open this file in a browser to use SPOT’s graphical user interface (GUI), which can be used without any programming. Note that this is not the same as interface1.js, which is the JavaScript that accompanies the GUI and does not need to be opened directly.

  2. main/prosodicHierarchy.js: This defines the prosodic and syntactic categories and their mappings that SPOT assumes, and can be modified locally by analysts who wish to include other prosodic categories. The default hierarchy includes three categories, ι (intonational phrase), φ (phonological phrase), and ω (phonological word). Note that adjusting the prosodic hierarchy will not automatically alter GEN to incorporate those new prosodic categories into the prosodic candidates.

  3. main/candidateGenerator.js: This file defines SPOT’s GEN function (described in Section 3).

  4. main/constraints: This folder contains all constraint definition files. Conceptually related constraints, such as different variations on the Binarity constraints, are defined in the same JS file (binarity.js, in the case of Binarity constraints). Look at these JS files to see the details of the algorithms SPOT uses to evaluate constraint violations. Users wishing to add their own constraints should save them to this folder, and then run build.sh to incorporate them into main/build to make them more accessible to the HTML files.

  5. main/build: The build folder contains concatenations of all the JavaScript files so that they can be easily imported into an HTML file for performing an analysis. The contents of main/build are created automatically by the bash shell script jsbuild.sh, located in main.

  6. main/lib: This folder contains utilities – currently just jszip.min, a library that converts a collection of csv files into a single zip file for convenient downloading.
Received: 2018-04-06
Accepted: 2018-07-12
Published Online: 2019-05-08

©2019 Walter de Gruyter GmbH, Berlin/Boston

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  2. Editorial
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  6. Automated tableau generation using SPOT (Syntax Prosody in Optimality Theory)
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  8. Morphology & Syntax
  9. A cross-linguistic perspective on the Right-Hand Head Rule: the rule and the exceptions
  10. Cross-linguistic evidence for cognitive universals in the noun phrase
  11. An introduction to Nanosyntax
  12. Nanosyntax and syncretism in multidimensional paradigms
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  18. Computational & Corpus Linguistics
  19. Effects of average and specific context probability on reduction of function words BE and HAVE
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  22. Cognitive Linguistics
  23. Language and creativity: a Construction Grammar approach to linguistic creativity
https://doi.org/10.1515/lingvan-2017-0051
Keywords for this article
syntax-prosody interface; Optimality Theory; Computational Tools in Phonology; prosody; OTWorkplace

Articles in the same Issue

  1. Editorial Note
  2. Editorial
  3. Phonetics & Phonology
  4. Antonym adjective pairs and prosodic iconicity: evidence from letter replications in an English blogger corpus
  5. Is there phonological feature priming?
  6. Automated tableau generation using SPOT (Syntax Prosody in Optimality Theory)
  7. The effect of prosodic focus varies by phrasal tones: the case of South Kyungsang Korean
  8. Morphology & Syntax
  9. A cross-linguistic perspective on the Right-Hand Head Rule: the rule and the exceptions
  10. Cross-linguistic evidence for cognitive universals in the noun phrase
  11. An introduction to Nanosyntax
  12. Nanosyntax and syncretism in multidimensional paradigms
  13. Psycholinguistics & Neurolinguistics
  14. Cross-linguistic influence in bilingual productions of the English past tense in Arabic heritage speakers of Australian English
  15. Sociolinguistics and Anthropological Linguistics
  16. TP-internal focus and dialectal variation: the case of the Focalizing Ser
  17. Language policy and language planning in mainland Southeast Asia: Myanmar and Lisu
  18. Computational & Corpus Linguistics
  19. Effects of average and specific context probability on reduction of function words BE and HAVE
  20. Studying variation in Romanian: deletion of the definite article -l in continuous speech
  21. Computational construction grammar for visual question answering
  22. Cognitive Linguistics
  23. Language and creativity: a Construction Grammar approach to linguistic creativity
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