dc.contributor.author |
Davel, MH
|
|
dc.contributor.author |
Barnard, E
|
|
dc.date.accessioned |
2012-01-18T08:29:17Z |
|
dc.date.available |
2012-01-18T08:29:17Z |
|
dc.date.issued |
2004-11 |
|
dc.identifier.citation |
Davel, MH and Barnard, E. 2004. Default-and-refinement approach to pronunciation prediction. 15th Annual Symposium of the Pattern Recognition Association of South Africa, Grabouw, South Africa, 25 to 26 November 2004 |
en_US |
dc.identifier.uri |
http://hdl.handle.net/10204/5501
|
|
dc.description |
15th Annual Symposium of the Pattern Recognition Association of South Africa, Grabouw, South Africa, 25 to 26 November 2004 |
en_US |
dc.description.abstract |
The authors define a novel g-to-p prediction algorithm that utilises the concept of a 'default phoneme': a grapheme which is realised as a specific phoneme significantly more often than as any other phoneme. They found that this approach results in an algorithm that performs well across a range from very small to large data sets. The authors evaluated the algorithm on two benchmarked databases (Fonilex and NETtalk) and found highly competitive performance in asymptotic accuracy, initial learning speed, and model compactness. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
PRASA 2004 |
en_US |
dc.subject |
Neural networks |
en_US |
dc.subject |
Decision trees |
en_US |
dc.subject |
Pronunciation |
en_US |
dc.subject |
Analogy models |
en_US |
dc.subject |
Instance based learning algorithms |
en_US |
dc.subject |
Dynamically expanding context |
en_US |
dc.subject |
PRASA 2004 |
en_US |
dc.title |
Default-and-refinement approach to pronunciation prediction |
en_US |
dc.type |
Conference Presentation |
en_US |
dc.identifier.apacitation |
Davel, M., & Barnard, E. (2004). Default-and-refinement approach to pronunciation prediction. PRASA 2004. http://hdl.handle.net/10204/5501 |
en_ZA |
dc.identifier.chicagocitation |
Davel, MH, and E Barnard. "Default-and-refinement approach to pronunciation prediction." (2004): http://hdl.handle.net/10204/5501 |
en_ZA |
dc.identifier.vancouvercitation |
Davel M, Barnard E, Default-and-refinement approach to pronunciation prediction; PRASA 2004; 2004. http://hdl.handle.net/10204/5501 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Davel, MH
AU - Barnard, E
AB - The authors define a novel g-to-p prediction algorithm that utilises the concept of a 'default phoneme': a grapheme which is realised as a specific phoneme significantly more often than as any other phoneme. They found that this approach results in an algorithm that performs well across a range from very small to large data sets. The authors evaluated the algorithm on two benchmarked databases (Fonilex and NETtalk) and found highly competitive performance in asymptotic accuracy, initial learning speed, and model compactness.
DA - 2004-11
DB - ResearchSpace
DP - CSIR
KW - Neural networks
KW - Decision trees
KW - Pronunciation
KW - Analogy models
KW - Instance based learning algorithms
KW - Dynamically expanding context
KW - PRASA 2004
LK - https://researchspace.csir.co.za
PY - 2004
T1 - Default-and-refinement approach to pronunciation prediction
TI - Default-and-refinement approach to pronunciation prediction
UR - http://hdl.handle.net/10204/5501
ER -
|
en_ZA |