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Research of the breathing characteristics when reading short song-poems

Author:
Yin, Xuechen
,
Yu, Hongzhi
Publisher:
IEEE
Year
: 2014
DOI: 10.1109/SNPD.2014.6888690
URI: https://libsearch.um.ac.ir:443/fum/handle/fum/1083386
Keyword(s): learning (artificial intelligence),n neural nets,n project management,n regression analysis,n software development management,n statistical testing,n time series,n GRNN prediction accuracy,n code reusage,n error relative magnitude,n fuzzy logic,n general regression neural network,n information-and-communication technology,n machine learning technique,n productivity management,n productivity prediction models,n programming language,n software pro
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    Research of the breathing characteristics when reading short song-poems

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contributor authorYin, Xuechen
contributor authorYu, Hongzhi
date accessioned2020-03-12T22:26:58Z
date available2020-03-12T22:26:58Z
date issued2014
identifier other7009830.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1083386
formatgeneral
languageEnglish
publisherIEEE
titleResearch of the breathing characteristics when reading short song-poems
typeConference Paper
contenttypeMetadata Only
identifier padid8220549
subject keywordslearning (artificial intelligence)
subject keywordsn neural nets
subject keywordsn project management
subject keywordsn regression analysis
subject keywordsn software development management
subject keywordsn statistical testing
subject keywordsn time series
subject keywordsn GRNN prediction accuracy
subject keywordsn code reusage
subject keywordsn error relative magnitude
subject keywordsn fuzzy logic
subject keywordsn general regression neural network
subject keywordsn information-and-communication technology
subject keywordsn machine learning technique
subject keywordsn productivity management
subject keywordsn productivity prediction models
subject keywordsn programming language
subject keywordsn software pro
identifier doi10.1109/SNPD.2014.6888690
journal titleudio, Language and Image Processing (ICALIP), 2014 International Conference on
filesize371464
citations0
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