The Levant is a region in the Near East with an impressive record of continuous human existence and major cultural developments since the Paleolithic period. Genetic and archeological studies present solid evidence placing the Middle East and the Arabian Peninsula as the first stepping-stone outside Africa. There is, however, little understanding of demographic changes in the Middle East, parti...

Here we report the unprecedented discovery of the skeleton of a ritually interred donkey with a metal horse bit in association with its teeth and saddlebag fastenings on its back. This discovery in the Middle Bronze Age III sacred precinct (1700/1650-1550 BCE) at Tel Haror, Israel, presents a unique combination of evidence for the early employment of equid harnessing equipment, both for chariot...

The Arabic language is a collection of spoken dialects with important phonological, morphological, lexical, and syntactic differences, along with a standard written language, Modern Standard Arabic (MSA). Since the spoken dialects are not officially written, it is very costly to obtain adequate corpora to use for training dialect NLP tools such as parsers. In this paper, we address the problem ...

The terms oral lichenoid reactions or oral lichenoid lesions refer to lesions histologically and clinically similar to oral lichen planus, though with the particularity that in these cases the underlying cause is identifiable. In addition, these lesions are described according to the causal factor involved, including alterations resulting from direct contact with dental restoration materials, d...

The goal of metadata extraction (MDE) is to enable technology that can take raw speech-to-text output and refine it into forms that are more useful to humans and to downstream automatic processes. Starting in 2003, a structural metadata annotation task was defined for English as part of the DARPA EARS Program. A significant new challenge for MDE is the addition of new languages. This paper repo...

In this paper we describe a system developed to identify a set of four regional Arabic dialects (Egyptian, Gulf, Levantine, North African) and Modern Standard Arabic (MSA) in a transcribed speech corpus. We competed under the team name MAZA in the Arabic Dialect Identification sub-task of the 2016 Discriminating between Similar Languages (DSL) shared task. Our system achieved an F1-score of 0.5...

Dialectal Arabic speech recognition is a difficult problem and is relatively less studied. In this paper, we propose a cross-dialectal Gaussian mixture model training criteria to transfer knowledge from one domain to the other by data sharing. Specifically, phone classification experiments on West Point Modern Standard Arabic Speech corpus and Babylon Levantine Arabic Speech corpus demonstrate ...