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1
JANA: A Human-Human Dialogues Corpus for Egyptian Dialect
Elmadany, AbdelRahim A.; Abdou, Sherif M.; Gheith, Mervat. - : Linguistic Data Consortium, 2016. : https://www.ldc.upenn.edu, 2016
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JANA: A Human-Human Dialogues Corpus for Egyptian Dialect ...
Elmadany, AbdelRahim A.; Abdou, Sherif M.; Gheith, Mervat. - : Linguistic Data Consortium, 2016
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3
Turn Segmentation into Utterances for Arabic Spontaneous Dialogues and Instance Messages ...
Abstract: Text segmentation task is an essential processing task for many of Natural Language Processing (NLP) such as text summarization, text translation, dialogue language understanding, among others. Turns segmentation considered the key player in dialogue understanding task for building automatic Human-Computer systems. In this paper, we introduce a novel approach to turn segmentation into utterances for Egyptian spontaneous dialogues and Instance Messages (IM) using Machine Learning (ML) approach as a part of automatic understanding Egyptian spontaneous dialogues and IM task. Due to the lack of Egyptian dialect dialogue corpus the system evaluated by our corpus includes 3001 turns, which are collected, segmented, and annotated manually from Egyptian call-centers. The system achieves F1 scores of 90.74% and accuracy of 95.98%. ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/1505.03081
https://dx.doi.org/10.48550/arxiv.1505.03081
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4
Towards Understanding Egyptian Arabic Dialogues ...
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5
Sentiment Analysis For Modern Standard Arabic And Colloquial ...
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6
Idioms-Proverbs Lexicon for Modern Standard Arabic and Colloquial Sentiment Analysis ...
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7
A stochastic Arabic diacritizer based on a hybrid of factorized and unfactorized textual features
In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 19 (2011) 1, 166-175
BLLDB
OLC Linguistik
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8
Beam search pruning in speech recognition using a posterior probability-based confidence measure
In: Speech communication. - Amsterdam [u.a.] : Elsevier 42 (2004) 3-4, 409-428
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