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Phonological Distance Measures
Nathan C Sanders1, Steven B Chin
1Department of Linguistics, Indiana University.
Journal of Quantitative Linguistics
|April 22, 2010
Summary
This study compares two computational methods for measuring phonological distance in pediatric cochlear implant users. Maximum likelihood distance shows high correlation with Levenshtein distance and manual transcriptions.
Area of Science:
- Computational linguistics
- Speech processing
- Audiology
Background:
- Phonological distance is crucial for understanding speech variations.
- Computational measures offer objective quantification.
- Pediatric cochlear implant users present unique speech intelligibility challenges.
Purpose of the Study:
- To compare two computational phonological distance measures: Levenshtein distance and maximum likelihood distance.
- To evaluate these measures against naive transcriptions of pediatric cochlear implant users' speech.
- To assess the feasibility of using these measures with lower-intelligibility speech.
Main Methods:
- Implemented Levenshtein distance (Nerbonne & Heeringa, 1997).
- Adapted Dunning's (1994) language classifier for maximum likelihood distance.
- Collected and transcribed speech data from pediatric cochlear implant users.
- Correlated computational measures with manual transcriptions.
Main Results:
- Maximum likelihood distance demonstrated a high correlation with Levenshtein distance.
- Both computational measures correlated highly with naive transcriptions.
- The maximum likelihood distance measure proved effective for the lower-intelligibility speech corpus.
Conclusions:
- Maximum likelihood distance is a viable and highly correlated measure for phonological distance in pediatric cochlear implant speech.
- Computational phonological distance measures can be effectively applied to challenging speech corpora.
- This facilitates research on speech intelligibility in special populations.
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