Арабский

Statistical machine translation is quite ro- bust when it comes to the choice of in- put representation. It only requires con- sistency between training and testing. As a result, there …...

We present a novel method for predicting in- flected word forms for generating morpho- logically rich languages in machine trans- lation. We utilize a rich set of syntactic and morphological …...

In this paper we investigate named entity transliteration based on a phonetic scoring method. The phonetic method is computed using phonetic features and carefully designed pseudo features. The proposed method …...

AbstractThe MIT-LL/AFRL MT system implements a standard phrase-based, statistical translation model. It incorporates a number of extensions that improve performance for speech-based translation. During this evaluation our efforts focused on …...

For centuries, the deep connection between languages has brought about major discover- ies about human communication. In this pa- per we investigate how this powerful source of information can be …...

We explore the contribution of morphologi- cal features – both lexical and inflectional – to dependency parsing of Arabic, a morpho- logically rich language. Using controlled ex- periments, we find …...

The connection between part-of-speech (POS) categories and morphological properties is well-documented in linguistics but underuti- lized in text processing systems. This pa- per proposes a novel model for morphologi- cal …...

Microblogging services such as Twitter have become popular media for real-time user- created news reporting. Such communica- tion often happens in parallel in different lan- guages, e.g., microblog posts related …...

Arabic is a morphologically rich and complex language, which presents signifi- cant challenges for natural language pro- cessing and machine translation. In this paper, we describe an ongoing effort to …...

Learning from errors is a crucial aspect of improving expertise. Based on this no- tion, we discuss a robust statistical frame- work for analysing the impact of different error types …...

We investigate different ways of learning structured perceptron models for coref- erence resolution when using non-local features and beam search. Our experi- mental results indicate that standard tech- niques such …...

AbstractWe release a massive expansion of the paraphrase database (PPDB) that now includes a collection of paraphrases in 23 different languages. The resource is derived from large volumes of bilingual …...

AbstractMost state-of-the-art systems today produce morphological analysis based only on orthographic patterns. In contrast, we propose a model for unsupervised morphological analysis that integrates orthographic and semantic views of words. …...

AbstractThis paper describes the system used in SemEval-2017 Task 4 (Subtask A): Message Polarity Classification for both English and Arabic languages. Our proposed system is an ensemble of two layers, …...

AbstractPart-of-speech (POS) tagging for morphologically rich languages such as Arabic is a challenging problem because of their enormous tag sets. One reason for this is that in the tagging scheme …...

AbstractWe consider entity-level sentiment analysis in Arabic, a morphologically rich language with increasing resources. We present a system that is applied to complex posts written in response to Arabic newspaper …...

Neural machine translation (NMT) models are conventionally trained with fixed-size vocabu- laries to control the computational complexity and the quality of the learned word represen- tations. This, however, limits the …...

We introduce Arabic Data Science Toolkit (ADST), a framework for Arabic language feature extraction, designed for data scientists that may not be familiar with Arabic or natural language processing. The …...

The French Algerian Code-Switching Triggered corpus (FACST) was created in order to support a variety of studies in phonetics, prosody and natural language processing. The first aim of the FACST …...

In this paper we present the annotation scheme and parser results of the animacy feature in Russian and Arabic, two morphologically- rich languages, in the spirit of the universal dependency …...

AbstractWord segmentation is a low-level NLP task that is non-trivial for a considerable number of languages. In this paper, we present a sequence tagging framework and apply it to word …...

We present Wasim, a web-based tool for semi-automatic morphosyntactic annotation of inflectional languages resources. The tool features high flexibility in segmenting tokens, editing, diacritizing, and labelling tokens and segments. Text …...

AbstractRecurrent neural network grammars generate sentences using phrase-structure syntax and perform very well on both parsing and language modeling. To explore whether generative dependency models are similarly effective, we propose …...

AbstractThis paper describes our participation in SemEval-2020 Task 12: Multilingual Offensive Language Detection. We jointly-trained a single model by fine-tuning Multilingual BERT to tackle the task across all the proposed …...

AbstractThis paper describes the KS@LTH system for SemEval-2020 Task 12 OffensEval2: Multilingual Offensive Language Identification in Social Media. We compare mono- and multilingual models based on fine-tuning pre-trained transformer models …...

AbstractWord embeddings have been successfully trained in many languages. However, both intrinsic and extrinsic metrics are variable across languages, especially for languages that depart significantly from English in morphology and …...

AbstractWe introduce DivEMT, the first publicly available post-editing study of Neural Machine Translation (NMT) over a typologically diverse set of target languages. Using a strictly controlled setup, 18 professional translators …...

Most Word-Sense Disambiguation (WSD) systems rely on machine learning approaches that require large-scale corpora for effective training. So, the quality of a WSD system degrades when trained in a low-resource …...

AbstractWe present classifiers that can accurately predict the proficiency level of nonnative Hebrew learners. This is important for practical (mainly educational) applications, but the endeavor also sheds light on the …...

AbstractiSarcasmEval is the first shared task to target intended sarcasm detection: the data for this task was provided and labelled by the authors of the texts themselves. Such an approach …...

AbstractIn this paper, we define the task of gender rewriting in contexts involving two users (I and/or You) – first and second grammatical persons with independent grammatical gender preferences. We …...