title: Articulatory distinctiveness of vowels and consonants: a data-driven approach.
abstract: OBJECTIVE
  To quantify the articulatory distinctiveness of 8 major English vowels and 11 English consonants based on tongue and lip movement time series data using a data-driven approach.
  
  
  METHODS
  Tongue and lip movements of 8 vowels and 11 consonants from 10 healthy talkers were collected. First, classification accuracies were obtained using 2 complementary approaches: (a) Procrustes analysis and (b) a support vector machine. Procrustes distance was then used to measure the articulatory distinctiveness among vowels and consonants. Finally, the distance (distinctiveness) matrices of different vowel pairs and consonant pairs were used to derive articulatory vowel and consonant spaces using multidimensional scaling.
  
  
  RESULTS
  Vowel classification accuracies of 91.67% and 89.05% and consonant classification accuracies of 91.37% and 88.94% were obtained using Procrustes analysis and a support vector machine, respectively. Articulatory vowel and consonant spaces were derived based on the pairwise Procrustes distances.
  
  
  CONCLUSIONS
  The articulatory vowel space derived in this study resembled the long-standing descriptive articulatory vowel space defined by tongue height and advancement. The articulatory consonant space was consistent with feature-based classification of English consonants. The derived articulatory vowel and consonant spaces may have clinical implications, including serving as an objective measure of the severity of articulatory impairment.
authors.affiliation: Correspondence to Jun Wang, who is now at Callier Center for Communication Disorders, University of Texas at Dallas: wangjun@utdallas.edu.
authors.forename: Jun
authors.initials: J
authors.lastname: Wang
authors.forename: Jordan R
authors.initials: JR
authors.lastname: Green
authors.forename: Ashok
authors.initials: A
authors.lastname: Samal
authors.forename: Yana
authors.initials: Y
authors.lastname: Yunusova
mesh_terms: D000328:Adult; D001696:Biomechanical Phenomena / Q000502:physiology; D005260:Female; D006801:Humans; D008046:Lip / Q000502:physiology; D008875:Middle Aged; D009068:Movement / Q000502:physiology; D010699:Phonation / Q000502:physiology*; D010700:Phonetics; D013060:Speech / Q000502:physiology*; D013061:Speech Acoustics; D013065:Speech Intelligibility / Q000502:physiology*; D014059:Tongue / Q000502:physiology; D014831:Voice / Q000502:physiology*; D055815:Young Adult
keywords: Procrustes analysis; articulatory consonant space; articulatory vowel space; speech production; support vector machine