Linked Life Data

8125504

Source:http://linkedlifedata.com/resource/pubmed/id/8125504

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
1994-4-14
pubmed:abstractText
The evaluation of the degree of speech impairment and the utility of computer recognition of impaired speech are separately and independently performed. Particular attention is paid to the question concerning whether or not there is a relationship between naive listeners' subjective judgements of impaired speech and the performance of a laboratory version of a speech recognition system. It is a difficult task to relate a speech impairment rating with speech recognition accuracy. Towards this end, a statistical causal model is proposed. This model is very appealing in its structure to support inference, and thus can be applied to perform various assessments such as the success of automatic recognition of dysarthric speech. The application of this model is illustrated with a case study of a dysarthric speaker compared against a normal speaker serving as a control.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0018-9294
pubmed:author
pubmed:issnType
Print
pubmed:volume
40
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1282-98
pubmed:dateRevised
2009-11-11
pubmed:meshHeading
pubmed:year
1993
pubmed:articleTitle
A statistical causal model for the assessment of dysarthric speech and the utility of computer-based speech recognition.
pubmed:affiliation
Department of Computer Science, Queens College, Flushing, NY 11367.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't