In this paper, we present the details of creating a pilot Arabic proposition bank (Propbank). Propbanks exist for both English and Chinese. However the morphological and syntactic expression of linguistic phenomena in Arabic yield a very different type of process in creating an Arabic propbank. Hence, we highlight those characteristics of Arabic that make creating a propbank for the language a ...

In this article we present Curras, the first morphologically annotated corpus of the Palestinian Arabic dialect. Palestinian Arabic is one of the many primarily spoken dialects of the Arabic language. Arabic dialects are generally under-resourced compared to Modern Standard Arabic, the primarily written and official form of Arabic. We start in the article with a background description that situ...

The performances of general and Arabic search engines were compared based on their ability to retrieve morphologically related Arabic terms. The findings highlight the importance of making users aware of what they miss by using the general engines, underscoring the need to modify these engines to better handle Arabic queries.

We present the results of our Arabic and English runs at the TAC 2011 Multilingual summarisation (MultiLing) task. We participated with centroid-based clustering for multidocument summarisation. The automatically generated Arabic and English summaries were evaluated by human participants and by two automatic evaluation metrics, ROUGE and AutoSummENG. The results are compared with the other syst...

Developments in Arabic information retrieval did not follow the increasing use of the Arabic Web during the last decade. Semantic indexing in a language with high inflectional morphology, such as Arabic, is not a trivial task and requires a text analysis in the original language. Excepting cross-language retrieval methods or limited studies, the main efforts, for developing semantic analysis me...

This paper presents an ESN-based Arabic phoneme recognition system trained with supervised, forced and combined supervised/forced supervised learning algorithms. Mel-Frequency Cepstrum Coefficients (MFCCs) and Linear Predictive Code (LPC) techniques are used and compared as the input feature extraction technique. The system is evaluated using 6 speakers from the King Abdulaziz Arabic Phonetics ...