Stochastic phonological grammars and acceptability
In foundational works of generative phonology it is claimed that subjects can reliably discriminate between possible but non-occurring words and words that could not be English. In this paper we examine the use of a probabilistic phonological parser for words to model experimentally-obtained judgeme...
| Príomhchruthaitheoirí: | , |
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| Formáid: | Journal article |
| Teanga: | English |
| Foilsithe / Cruthaithe: |
Association for Computational Linguistics
1997
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| Ábhair: |
| _version_ | 1826288039895236608 |
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| author | Coleman, J Pierrehumbert, J |
| author_facet | Coleman, J Pierrehumbert, J |
| author_sort | Coleman, J |
| collection | OXFORD |
| description | In foundational works of generative phonology it is claimed that subjects can reliably discriminate between possible but non-occurring words and words that could not be English. In this paper we examine the use of a probabilistic phonological parser for words to model experimentally-obtained judgements of the acceptability of a set of nonsense words. We compared various methods of scoring the goodness of the parse as a predictor of acceptability. We found that the probability of the worst part is not the best score of acceptability, indicating that classical generative phonology and Optimality Theory miss an important fact, as these approaches do not recognise a mechanism by which the frequency of well-formed parts may ameliorate the unacceptability of low-frequency parts. We argue that probabilistic generative grammars are demonstrably a more psychologically realistic model of phonological competence than standard generative phonology or Optimality Theory. |
| first_indexed | 2024-03-07T02:07:42Z |
| format | Journal article |
| id | oxford-uuid:9f8cd391-0beb-40f9-9ec0-4112bd08e165 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T02:07:42Z |
| publishDate | 1997 |
| publisher | Association for Computational Linguistics |
| record_format | dspace |
| spelling | oxford-uuid:9f8cd391-0beb-40f9-9ec0-4112bd08e1652022-03-27T00:58:44ZStochastic phonological grammars and acceptabilityJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:9f8cd391-0beb-40f9-9ec0-4112bd08e165Computational LinguisticsLinguisticsEnglishOxford University Research Archive - ValetAssociation for Computational Linguistics1997Coleman, JPierrehumbert, JIn foundational works of generative phonology it is claimed that subjects can reliably discriminate between possible but non-occurring words and words that could not be English. In this paper we examine the use of a probabilistic phonological parser for words to model experimentally-obtained judgements of the acceptability of a set of nonsense words. We compared various methods of scoring the goodness of the parse as a predictor of acceptability. We found that the probability of the worst part is not the best score of acceptability, indicating that classical generative phonology and Optimality Theory miss an important fact, as these approaches do not recognise a mechanism by which the frequency of well-formed parts may ameliorate the unacceptability of low-frequency parts. We argue that probabilistic generative grammars are demonstrably a more psychologically realistic model of phonological competence than standard generative phonology or Optimality Theory. |
| spellingShingle | Computational Linguistics Linguistics Coleman, J Pierrehumbert, J Stochastic phonological grammars and acceptability |
| title | Stochastic phonological grammars and acceptability |
| title_full | Stochastic phonological grammars and acceptability |
| title_fullStr | Stochastic phonological grammars and acceptability |
| title_full_unstemmed | Stochastic phonological grammars and acceptability |
| title_short | Stochastic phonological grammars and acceptability |
| title_sort | stochastic phonological grammars and acceptability |
| topic | Computational Linguistics Linguistics |
| work_keys_str_mv | AT colemanj stochasticphonologicalgrammarsandacceptability AT pierrehumbertj stochasticphonologicalgrammarsandacceptability |