Universal Features in Phonological Neighbor Networks
Human speech perception involves transforming a countinuous acoustic signal into discrete linguistically meaningful units (phonemes) while simultaneously causing a listener to activate words that are similar to the spoken utterance and to each other. The Neighborhood Activation Model posits that pho...
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| Format: | Article |
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MDPI AG
2018-07-01
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| Series: | Entropy |
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| Online Access: | http://www.mdpi.com/1099-4300/20/7/526 |
| _version_ | 1798039742013505536 |
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| author | Kevin S. Brown Paul D. Allopenna William R. Hunt Rachael Steiner Elliot Saltzman Ken McRae James S. Magnuson |
| author_facet | Kevin S. Brown Paul D. Allopenna William R. Hunt Rachael Steiner Elliot Saltzman Ken McRae James S. Magnuson |
| author_sort | Kevin S. Brown |
| collection | DOAJ |
| description | Human speech perception involves transforming a countinuous acoustic signal into discrete linguistically meaningful units (phonemes) while simultaneously causing a listener to activate words that are similar to the spoken utterance and to each other. The Neighborhood Activation Model posits that phonological neighbors (two forms [words] that differ by one phoneme) compete significantly for recognition as a spoken word is heard. This definition of phonological similarity can be extended to an entire corpus of forms to produce a phonological neighbor network (PNN). We study PNNs for five languages: English, Spanish, French, Dutch, and German. Consistent with previous work, we find that the PNNs share a consistent set of topological features. Using an approach that generates random lexicons with increasing levels of phonological realism, we show that even random forms with minimal relationship to any real language, combined with only the empirical distribution of language-specific phonological form lengths, are sufficient to produce the topological properties observed in the real language PNNs. The resulting pseudo-PNNs are insensitive to the level of lingustic realism in the random lexicons but quite sensitive to the shape of the form length distribution. We therefore conclude that “universal” features seen across multiple languages are really string universals, not language universals, and arise primarily due to limitations in the kinds of networks generated by the one-step neighbor definition. Taken together, our results indicate that caution is warranted when linking the dynamics of human spoken word recognition to the topological properties of PNNs, and that the investigation of alternative similarity metrics for phonological forms should be a priority. |
| first_indexed | 2024-04-11T21:57:56Z |
| format | Article |
| id | doaj.art-cb3e1030fe3f41f680e9bb34e0451992 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-11T21:57:56Z |
| publishDate | 2018-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-cb3e1030fe3f41f680e9bb34e04519922022-12-22T04:01:02ZengMDPI AGEntropy1099-43002018-07-0120752610.3390/e20070526e20070526Universal Features in Phonological Neighbor NetworksKevin S. Brown0Paul D. Allopenna1William R. Hunt2Rachael Steiner3Elliot Saltzman4Ken McRae5James S. Magnuson6Department of Biomedical Engineering, University of Connecticut, Storrs, CT 06269, USADepartment of Psychological Sciences, University of Connecticut, Storrs, CT 06269, USADepartment of Biomedical Engineering, University of Connecticut, Storrs, CT 06269, USADepartment of Psychological Sciences, University of Connecticut, Storrs, CT 06269, USADepartment of Physical Therapy and Athletic Training, Boston University, Boston, MA 02215, USADepartment of Psychology, University of Western Ontario, London, ON N6A 5C2, CanadaConnecticut Institute for the Brain & Cognitive Sciences, Storrs, CT 06269, USAHuman speech perception involves transforming a countinuous acoustic signal into discrete linguistically meaningful units (phonemes) while simultaneously causing a listener to activate words that are similar to the spoken utterance and to each other. The Neighborhood Activation Model posits that phonological neighbors (two forms [words] that differ by one phoneme) compete significantly for recognition as a spoken word is heard. This definition of phonological similarity can be extended to an entire corpus of forms to produce a phonological neighbor network (PNN). We study PNNs for five languages: English, Spanish, French, Dutch, and German. Consistent with previous work, we find that the PNNs share a consistent set of topological features. Using an approach that generates random lexicons with increasing levels of phonological realism, we show that even random forms with minimal relationship to any real language, combined with only the empirical distribution of language-specific phonological form lengths, are sufficient to produce the topological properties observed in the real language PNNs. The resulting pseudo-PNNs are insensitive to the level of lingustic realism in the random lexicons but quite sensitive to the shape of the form length distribution. We therefore conclude that “universal” features seen across multiple languages are really string universals, not language universals, and arise primarily due to limitations in the kinds of networks generated by the one-step neighbor definition. Taken together, our results indicate that caution is warranted when linking the dynamics of human spoken word recognition to the topological properties of PNNs, and that the investigation of alternative similarity metrics for phonological forms should be a priority.http://www.mdpi.com/1099-4300/20/7/526networksneighborhood activation modelphonologyphonological neighbor network |
| spellingShingle | Kevin S. Brown Paul D. Allopenna William R. Hunt Rachael Steiner Elliot Saltzman Ken McRae James S. Magnuson Universal Features in Phonological Neighbor Networks Entropy networks neighborhood activation model phonology phonological neighbor network |
| title | Universal Features in Phonological Neighbor Networks |
| title_full | Universal Features in Phonological Neighbor Networks |
| title_fullStr | Universal Features in Phonological Neighbor Networks |
| title_full_unstemmed | Universal Features in Phonological Neighbor Networks |
| title_short | Universal Features in Phonological Neighbor Networks |
| title_sort | universal features in phonological neighbor networks |
| topic | networks neighborhood activation model phonology phonological neighbor network |
| url | http://www.mdpi.com/1099-4300/20/7/526 |
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