208,474 research outputs found

    Towards Understanding Egyptian Arabic Dialogues

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    Labelling of user's utterances to understanding his attends which called Dialogue Act (DA) classification, it is considered the key player for dialogue language understanding layer in automatic dialogue systems. In this paper, we proposed a novel approach to user's utterances labeling for Egyptian spontaneous dialogues and Instant Messages using Machine Learning (ML) approach without relying on any special lexicons, cues, or rules. Due to the lack of Egyptian dialect dialogue corpus, the system evaluated by multi-genre corpus includes 4725 utterances for three domains, which are collected and annotated manually from Egyptian call-centers. The system achieves F1 scores of 70. 36% overall domains.Comment: arXiv admin note: substantial text overlap with arXiv:1505.0308

    Electrophysiological and kinematic correlates of communicative intent in the planning and production of pointing gestures and speech

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    Acknowledgements We thank Albert Russel for assistance in setting up the experiments, and Charlotte Paulisse for help in data collection.Peer reviewedPublisher PD

    Cross-Linguistic Influence in the Bilingual Mental Lexicon: Evidence of Cognate Effects in the Phonetic Production and Processing of a Vowel Contrast.

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    The present study examines cognate effects in the phonetic production and processing of the Catalan back mid-vowel contrast (/o/-/ɔ/) by 24 early and highly proficient Spanish-Catalan bilinguals in Majorca (Spain). Participants completed a picture-naming task and a forced-choice lexical decision task in which they were presented with either words (e.g., /bɔsk/ "forest") or non-words based on real words, but with the alternate mid-vowel pair in stressed position ((*)/bosk/). The same cognate and non-cognate lexical items were included in the production and lexical decision experiments. The results indicate that even though these early bilinguals maintained the back mid-vowel contrast in their productions, they had great difficulties identifying non-words and real words based on the identity of the Catalan mid-vowel. The analyses revealed language dominance and cognate effects: Spanish-dominants exhibited higher error rates than Catalan-dominants, and production and lexical decision accuracy were also affected by cognate status. The present study contributes to the discussion of the organization of early bilinguals' dominant and non-dominant sound systems, and proposes that exemplar theoretic approaches can be extended to include bilingual lexical connections that account for the interactions between the phonetic and lexical levels of early bilingual individuals

    A Robust Transformation-Based Learning Approach Using Ripple Down Rules for Part-of-Speech Tagging

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    In this paper, we propose a new approach to construct a system of transformation rules for the Part-of-Speech (POS) tagging task. Our approach is based on an incremental knowledge acquisition method where rules are stored in an exception structure and new rules are only added to correct the errors of existing rules; thus allowing systematic control of the interaction between the rules. Experimental results on 13 languages show that our approach is fast in terms of training time and tagging speed. Furthermore, our approach obtains very competitive accuracy in comparison to state-of-the-art POS and morphological taggers.Comment: Version 1: 13 pages. Version 2: Submitted to AI Communications - the European Journal on Artificial Intelligence. Version 3: Resubmitted after major revisions. Version 4: Resubmitted after minor revisions. Version 5: to appear in AI Communications (accepted for publication on 3/12/2015

    Improving the translation environment for professional translators

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    When using computer-aided translation systems in a typical, professional translation workflow, there are several stages at which there is room for improvement. The SCATE (Smart Computer-Aided Translation Environment) project investigated several of these aspects, both from a human-computer interaction point of view, as well as from a purely technological side. This paper describes the SCATE research with respect to improved fuzzy matching, parallel treebanks, the integration of translation memories with machine translation, quality estimation, terminology extraction from comparable texts, the use of speech recognition in the translation process, and human computer interaction and interface design for the professional translation environment. For each of these topics, we describe the experiments we performed and the conclusions drawn, providing an overview of the highlights of the entire SCATE project
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