Name
Abstract | ||
|---|---|---|
The articulatory distinctiveness among vowels has been frequently characterized descriptively based on tongue height and front-back position; however, very few empirical methods have been proposed to characterize vowels based on time-varying articulatory characteristics. Such information is not only needed to improve knowledge about the articulation of vowels but also to determine the contribution of articulatory imprecision to poor speech intelligibility. In this paper, a novel statistical shape analysis was used to derive a vowel space that depicted the quantified articulatory distinctiveness among vowels based on tongue and lip movements. The effectiveness of the approach was supported by vowel classification accuracy of up to 91.7%. The theoretical relevance and clinical implication of the derived vowel space were discussed. |
Year | Venue | Keywords |
|---|---|---|
2011 | 12TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2011 (INTERSPEECH 2011), VOLS 1-5 | speech production, articulatory vowel space, Procrustes analysis, multi-dimensional scaling |
Field | DocType | Citations |
Multidimensional scaling,Statistical shape analysis,Computer science,Poor speech,Procrustes analysis,Speech recognition,Vowel,Speech production,Optimal distinctiveness theory,Intelligibility (communication) | Conference | 5 |
PageRank | References | Authors |
0.60 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jun Wang | 1 | 144 | 15.26 |
| Jordan R. Green | 2 | 35 | 7.19 |
| A Samal | 3 | 1033 | 213.54 |
| David Marx | 4 | 5 | 0.60 |