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Comparison of algorithms to divide noisy phone sequences into syllables for automatic unconstrained English speaking proficiency scoring
David O. Johnson
,
Okim Kang
English
Research output
:
Contribution to journal
›
Article
›
peer-review
6
Scopus citations
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Dive into the research topics of 'Comparison of algorithms to divide noisy phone sequences into syllables for automatic unconstrained English speaking proficiency scoring'. Together they form a unique fingerprint.
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Keyphrases
Utterance
100%
English Proficiency
100%
Algorithm Comparison
100%
Genetic Algorithm
66%
Oral Proficiency
66%
Vowels
66%
Radio News
66%
University Radio
66%
Boston
66%
News Corpus
66%
Syllabification
66%
Syllabic Consonants
66%
Hidden Markov Model
33%
Pearson Correlation
33%
Consonants
33%
Boundary Based
33%
Specific Category
33%
Temporal Alignment
33%
Syllable Boundary
33%
Examiner
33%
Sonority
33%
Proficiency Score
33%
Arts and Humanities
Proficiency
100%
Utterance
50%
Corpus
33%
Oral
33%
Grouping
33%
Radio News
33%
Boston
33%
syllabic consonant
33%
Syllabification
33%
Application
16%
Temporal
16%
On-set
16%
Sonority
16%
Consonant clusters
16%