Articulatory Performance in Dysarthria: Using a Data-Driven Approach to Estimate Articulatory Demands and Deficits is a research paper published in Brain Sciences (2022). On theSindex it has a DataRank of 0. It has been cited 9 times.
Scored on demand from live citation data
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
NIH-NIDCD
Grant: 1R15DC016383
NIH-NIDCD
Grant: R21DC019952-01
NIH-NIDCD
Grant: R03DC015075
NIH-NIDCD
Grant: R01DC019648-01A1
NIDCD NIH HHS
Grant: R01 DC019648
NIH HHS
Grant: R15DC016383
NICHD NIH HHS
Grant: P50 HD103537
NIDCD NIH HHS
Grant: R21 DC019952
National Institutes of Health
Grant: 1R15DC016383-01
A Systematic Investigation of Phonetic Complexity Effects on Articulatory Motor Performance in Progressive Dysarthria
National Institutes of Health
Grant: 5R01DC019648-04
A taxonomic articulation-focused approach to dysarthria classification
National Institutes of Health
Grant: 1R21DC019952-01A1
Generating Personalized Synthetic Speech for Progressive Dysarthria Using Severity-Appropriate Adaptation Strategies for Neural Text-to-Speech and Voice Conversion
National Institutes of Health
Grant: 1R03DC015075-01A1
Tongue- and Jaw-Specific Contributions to Vowel Acoustic Changes: Towards a Mechanistic Model of Intelligibility Loss and Recovery in Dysarthria
FWCI
0.66
Citation Percentile
0.7%
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals