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  5. The effect of phoneme distribution on perceptual similarity in English
 
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The effect of phoneme distribution on perceptual similarity in English

Author(s)
O'Neill, E. (Emma)  
Carson-Berndsen, Julie  
Uri
http://hdl.handle.net/10197/11508
Date Issued
2019-09-19
Date Available
2020-08-27T11:48:06Z
Abstract
This paper investigates the extent to which native speaker perceptions regarding the similarity between phonemes of English are influenced by their distributional properties. A similarity hierarchy model based on the distribution of consonantal phonemes in the English language was generated by creating phoneme-embeddings from contextual information. We compare this to similarity models based on phonological feature theory and on native speaker perception. Characteristics of the perception-based model are shown to appear in the distribution-based model whilst not being captured by the feature-based model. This not only provides evidence of similarity perceptions being influenced by distributional properties but is an argument for incorporating distributional information alongside phonological features when modelling perceptual similarity.
Type of Material
Conference Publication
Publisher
ISCA
Copyright (Published Version)
2019 ISCA
Subjects

Phonology

Phenome similarity

Distribution

Perception

DOI
10.21437/Interspeech.2019-3042
Web versions
https://www.interspeech2019.org/
Language
English
Status of Item
Peer reviewed
Journal
The 20th Annual Conference of the International Speech Communication Association (INTERSPEECH 2019): Crossroads of Speech and Language
Conference Details
The 20th Annual Conference of the International Speech Communication Association (Interspeech 2019), Graz, Austria, 15-19 September 2019
ISBN
9781615676927
ISSN
2308-457X
1990-9772
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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INTERSPEECH_2019.pdf

Size

138.86 KB

Format

Adobe PDF

Checksum (MD5)

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Owning collection
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
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