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Assessing surface phonological specification through simulation and classification of phonetic trajectories
- Source :
- Phonology. 35:481-522
- Publication Year :
- 2018
- Publisher :
- Cambridge University Press (CUP), 2018.
-
Abstract
- Many previous studies have argued that phonology may leave some phonetic dimensions unspecified in surface representations. We introduce computational tools for assessing this possibility though simulation and classification of phonetic trajectories. The empirical material used to demonstrate the approach comes from electromagnetic articulography recordings of high-vowel devoicing in Japanese. Using Discrete Cosine Transform, tongue-dorsum movement trajectories are decomposed into a small number of frequency components (cosines differing in frequency and amplitude) that correspond to linguistically meaningful signal modulations, i.e. articulatory gestures. Stochastic generators of competing phonological hypotheses operate in this frequency space. Distributions over frequency components are used to simulate (i) the vowel-present trajectories and (ii) the vowel-absent trajectories. A Bayesian classifier trained on simulations assigns posterior probabilities to unseen data. Results indicate that /u/ is optionally produced without a vowel-height specification in Tokyo Japanese and that the frequency of such targetlessness varies systematically across phonological environments.
- Subjects :
- 060201 languages & linguistics
Surface (mathematics)
Linguistics and Language
Computer science
Speech recognition
Posterior probability
SIGNAL (programming language)
Phonology
06 humanities and the arts
Language and Linguistics
030507 speech-language pathology & audiology
03 medical and health sciences
Naive Bayes classifier
Amplitude
0602 languages and literature
Discrete cosine transform
0305 other medical science
Articulatory gestures
Subjects
Details
- ISSN :
- 14698188 and 09526757
- Volume :
- 35
- Database :
- OpenAIRE
- Journal :
- Phonology
- Accession number :
- edsair.doi...........13453142af9ac17ef3f842d140c1eb65
- Full Text :
- https://doi.org/10.1017/s0952675718000131