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[9001731.] رقم البحث : 9001731 - |
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A Prototype Theory-Based Study of Crimes in the English and Arabic Societies Using Web-as-Corpus / |
| تخصص البحث : Large Corpora |
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هندسة اللغة: / العدد 2 - مجلد (4) - سبتمبر 2017 |
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تاريخ تقديم البحث 03/10/2017 |
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تاريخ قبول البحث 03/10/2017 |
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عدد صفحات البحث 9 |
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Fadia A. A. M. Badawi ( fadia_ahmed@rocketmail.com - ) - مؤلف رئيسي |
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KhaledElghamry ( elghamryk@gmail.com - ) |
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FayrouzFouad ( fayrouzff@yahoo.com - ) |
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Prototype Theory, Categorization, Corpora, Semantic Hierarchy, Cognitive semantics; Crimes. |
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Abstract: Drawing on the classified prototypes of semantic categories, this paper uses the principles of the prototype theory to cross-culturally explore the hierarchical prototypes of crimes in web-booted Arabic and English corpora. The study compares the conceptualization and categorization of crimes in the Arabic and English worlds. For doing so, four domains ‘com, org, info and edu’ are explored over the past seven years for differentiating the individual mentality from the institutional mentalities. The study uses the web as corpus to investigate the inductive pattern ‘crime* such as’ in three web domains: ‘.com’, ‘.org’ and ‘.edu’ in Arabic and English. The collected data is analyzed using AntConc software program. Indicated statistical tests are calculated to measure the universality of conceptualizing emotions across Arabic and English speaking worlds. The study explores the validity of using Rosch’s prototype theory (1975) in determining the dynamically changing categorization of criminal acts. It also tests the authenticity of using Web-as-Corpus, which is a very straightforward tool, in attaining so. Results reveal that there is an Arabic-English agreement on defining the basic levels of the concept crime. However, few sporadic differences exist and are subject of cultural differences between the oriental and occidental moralities. The principles of prototype theory are also valid as regards the metamorphosis of conceptualizing a concept at the folkloric and expert levels. This holds true as regards the Arabic and English data of this study. |
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[9001733.] رقم البحث : 9001733 - |
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Toward Building a Comprehensive Phrase-based English-Arabic Statistical Machine Translation System / ٍٍٍ |
| تخصص البحث : Machine Translation |
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هندسة اللغة: / العدد 2 - مجلد (4) - سبتمبر 2017 |
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تاريخ تقديم البحث 03/10/2017 |
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تاريخ قبول البحث 03/10/2017 |
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عدد صفحات البحث 17 |
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Sara Ebrahim ( sara.elkafrawy@gmail.com - ) - مؤلف رئيسي |
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Doaa Higazyy ( doaa.hegazy@cis.asu.edu.eg - ) |
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Mostafa G. M. Mostafa ( mgmostafa@cis.asu.edu.eg - ) |
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Samhaa R. El-Beltagy ( samhaa@computer.org - ) |
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Machine Translation, Arabic Natural Language Processing, Phrase-based, Statistical Machine Translation. |
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This paper explores a phrase-based statistical machine translation (PBSMT) pipeline for English-Arabic (En-Ar) language pair. The work surveys the most recent experiments conducted to enhance Arabic machine translation in the En-Ar direction. It also focuses on free datasets and linguistically motivated ideas that enhance phrase-based En-Ar statistical machine translation (SMT) as it is as aims to use those only in order to build a large scale En-Ar SMT system. In addition, the paper highlights Arabic linguistic challenges in Machine Translation (MT) in general. This paper can be considered a guide for building an En-Ar PBSMT system. Furthermore, the presented pipeline can be generalized to any language pairs. |
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[9001738.] رقم البحث : 9001738 - |
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Establishing Dynamic Ontology for Agriculture Domain / Ontology |
| تخصص البحث : Semantic Web and Ontology Languages |
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هندسة اللغة: / العدد 2 - مجلد (4) - سبتمبر 2017 |
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تاريخ تقديم البحث 12/10/2017 |
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تاريخ قبول البحث 12/10/2017 |
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عدد صفحات البحث 18 |
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سوزان فيصل أمين اللقوة ( fisalsusan@yahoo.com - ) - مؤلف رئيسي |
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بسنت محمد الكفراوى ( passentmk@gmail.com - ) |
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Keywords: Ontology, Knowledge Representation, Matching and Merging Ontology |
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Abstract: This paper presents semi-automated system for establishing integrated ontology by merging two ontologies. It uses two processes: matching and merging. Matching process uses string-based technique, this technique uses four methods: exact method to detect identical terms, and substring, suffix and prefix methods to compare between terms. Using these four methods altogether improve the effectiveness of matching process, matching process uses also language-based techniques; this technique uses WordNet Method to detect terms that have the same meaning. This technique improves also the effectiveness of matching process. The proposed system presents a merging method of taxonomies in effective way. The system solves redundancy and inconsistency problem in integrated ontology.The proposed system is applied on the agricultural domain for Faba Bean crop to get an integrated ontology, it can be applied also on all crops whatever field crops or horticulture crops. The evaluation of the system shows that the performance of the system has high quality. The comparison of the proposed system and other systems shows that the proposed system has advantage of using five matching methods for mapping between terms that make the mapping between terms more perfect and efficient. The merger algorithm solves problems which appeared in other systems. |
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[9001739.] رقم البحث : 9001739 - |
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Enhancement Quality and Accuracy of Speech Recognition System Using Multimodal Audio-Visual Speech signal / |
| تخصص البحث : Speech Processing, Recognition and Synthesis |
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هندسة اللغة: / العدد 2 - مجلد (4) - سبتمبر 2017 |
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تاريخ تقديم البحث 12/10/2017 |
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تاريخ قبول البحث 12/10/2017 |
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عدد صفحات البحث 14 |
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اسلام المغربى ( eem00@fayoum.edu.eg - ) - مؤلف رئيسي |
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عمرو جودى ( amg00@fayoum.edu.eg - ) |
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محمدهشام فاروق ( mhesham@eng.cu.edu.eg - ) |
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Keywords- AV-ASR, HMM, HTK, MFCC, DCT, PCA, MATLAB, GRID |
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Abstract— Most developments in speech-based automatic recognition have relied on acoustic speech as the sole input signal, disregarding its visual counterpart. However, recognition based on acoustic speech alone can be afflicted with deficiencies that prevent its use in many real-world applications, particularly under adverse conditions. The combination of auditory and visual modalities promises higher recognition accuracy and robustness than can be obtained with a single modality. Multimodal recognition is therefore acknowledged as a vital component of the next generation of spoken language systems. This paper aims to build a connected-words audio visual speech recognition system (AV-ASR) for English language that uses both acoustic and visual speech information to improve the recognition performance. Initially, Mel frequency cepstral coefficients (MFCCs) have been used to extract the audio features from the speech-files. For the visual counterpart, the Discrete Cosine Transform (DCT) Coefficients have been used to extract the visual feature from the speaker’s mouth region and Principle Component Analysis (PCA) have been used for dimensionality reduction purpose. These features are then concatenated with traditional audio ones, and the resulting features are used for training hidden Markov models (HMMs) parameters using word level acoustic models. The system has been developed using hidden Markov model toolkit (HTK) that uses hidden Markov models (HMMs) for recognition. The potential of the suggested approach is demonstrated by a preliminary experiment on the GRID sentence database one of the largest databases available for audio-visual recognition system, which contains continuous English voice commands for a small vocabulary task. The experimental results show that the proposed Audio Video Speech Recognizer (AV-ASR) system exhibits higher recognition rate in comparison to an audio-only recognizer as well as it indicates robust performance. An increase of success rate by 4% for the grammar based word recognition system overall speakers is achieved for speaker independent test. |
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