Implementing a “Cue-based Features” approach to the phonetics/phonology interface

Models of the phonetics/phonology interface have typically dealt with phonetic detail in a quite idealized way, for instance by placing exemplars in a one or two-dimensional idealized phonetic cue space. This paper explores a more phonetically realistic approach to modeling phonological cues building on a “Cue-based Features” account of perceptual cue trading and the interface between phonetic cues and phonological features. We train non-negative matrix factorization over large speech corpora to discover spectrotemporal patterns that are potential acoustic cues for phonological contrast, and then we use linear discriminant analysis to find combinations of cues that can be optimally used to specify the value of a phonological feature. We present a preliminary study of plosive voicing cues, and the resulting models reveal that the cues trade with each other across exemplars and that they encode information that is temporally spread beyond the segment’s acoustic boundaries.

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Publication Details

Journal
The Journal of the Acoustical Society of America
Published
2025-04-01
DOI
https://doi.org/10.1121/10.0037785
Primary Topic
Speech Recognition and Synthesis
Type
article
Field-Weighted Citation Impact
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article

Implementing a “Cue-based Features” approach to the phonetics/phonology interface

Alexandra M. Pfiffner, Keith Johnson
The Journal of the Acoustical Society of America
Speech Recognition and Synthesis
article

Implementing a “Cue-based Features” approach to the phonetics/phonology interface

Alexandra M. Pfiffner, Keith Johnson
article en

Abstract

Models of the phonetics/phonology interface have typically dealt with phonetic detail in a quite idealized way, for instance by placing exemplars in a one or two-dimensional idealized phonetic cue space. This paper explores a more phonetically realistic approach to modeling phonological cues building on a “Cue-based Features” account of perceptual cue trading and the interface between phonetic cues and phonological features. We train non-negative matrix factorization over large speech corpora to discover spectrotemporal patterns that are potential acoustic cues for phonological contrast, and then we use linear discriminant analysis to find combinations of cues that can be optimally used to specify the value of a phonological feature. We present a preliminary study of plosive voicing cues, and the resulting models reveal that the cues trade with each other across exemplars and that they encode information that is temporally spread beyond the segment’s acoustic boundaries.

The Journal of the Acoustical Society of AmericaVol. 157(4_Supplement)
Berkeley College (US)
Reduced inequalities
Openalex Percentile: Top 90%
Speech Recognition and Synthesis
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