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    • The Pennsylvania State University CiteSeerX Archives (9)
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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 9 of 9 1 Cross-lingual acoustic modeling for dialectal Arabic speech recognition Mohamed Elmahdy; Rainer Gruhn; Wolfgang Minker... In: http://met.guc.edu.eg/Repository/Faculty/Publications/311/interspeech10.pdf (2010) BASE Show details 2 F0 ALIGNMENT PATTERNS IN ARABIC DIALECTS Mohamed Yeou; Mohamed Embarki; Sallal Al Maqtari... In: http://www.icphs2007.de/conference/Papers/1173/1173.pdf BASE Show details 3 Simplified guidelines for the creation of large scale dialectal arabic annotations Heba Elfardy; Mona Diab In: http://www.lrec-conf.org/proceedings/lrec2012/pdf/815_Paper.pdf BASE Show details 4 Token Level Identification of Linguistic Code Switching Heba El; M Diab In: http://aclweb.org/anthology/C/C12/C12-2029.pdf BASE Show details 5 A Transfer Learning Approach for Under-Resourced Arabic Dialects Speech Recognition Mohamed Elmahdy; Mark Hasegawa-johnson; Eiman Mustafawi In: http://www.isle.illinois.edu/sst/pubs/2013/ltc-065-mohamed.pdf BASE Show details 6 Developing an Egyptian Arabic Treebank: Impact of Dialectal Morphology on Annotation and Tool Development Mohamed Maamouri; Ann Bies; Seth Kulick... In: http://www.lrec-conf.org/proceedings/lrec2014/pdf/1145_Paper.pdf BASE Show details 7 YouDACC: the Youtube Dialectal Arabic Commentary Corpus Ahmed Salama; Houda Bouamor; Behrang Mohit... In: http://www.lrec-conf.org/proceedings/lrec2014/pdf/558_Paper.pdf BASE Show details 8 Development of a TV Broadcasts Speech Recognition Mohamed Elmahdy; Mark Hasegawa-johnsony; Eiman Mustafawi In: http://www.isle.illinois.edu/sst/pubs/2014/elmahdy_qa_lrec14.pdf Abstract: A major problem with dialectal Arabic speech recognition is due to the sparsity of speech resources. In this paper, a transfer learning framework is proposed to jointly use a large amount of Modern Standard Arabic (MSA) data and little amount of dialectal Arabic data to improve acoustic and language modeling. The Qatari Arabic (QA) dialect has been chosen as a typical example for an under-resourced Arabic dialect. A wide-band speech corpus has been collected and transcribed from several Qatari TV series and talk-show programs. A large vocabulary speech recognition baseline system was built using the QA corpus. The proposed MSA-based transfer learning technique was performed by applying orthographic normalization, phone mapping, data pooling, acoustic model adaptation, and system combination. The proposed approach can achieve more than 28 % relative reduction in WER. Keyword: dialectal Arabic; speech recognition; transfer learning URL: http://www.isle.illinois.edu/sst/pubs/2014/elmahdy_qa_lrec14.pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.641.905 BASE Hide details 9 A Multi-Dialect, Multi-Genre Corpus of Informal Written Arabic Ryan Cotterell; Chris Callison-burch In: http://hubal.cs.jhu.edu/papers/arabic-dialect-corpus-2.pdf BASE Show details

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