Search results for "Language processing"

showing 10 items of 421 documents

Recensión: "Key terms in second language acquisition"

2011

Recensión: "Key terms in second language acquisition. Bill van Petten and Alessandro g. Benati. Continuum International Publishing Group, 2010."

Linguistics and Languagebusiness.industryComputer scienceL2Key termscomputer.software_genreSecond-language acquisitionLanguage and LinguisticsEducationKey termsRecensionesArtificial intelligencebusinesscomputerNatural language processingPorta Linguarum Revista Interuniversitaria de Didáctica de las Lenguas Extranjeras
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Function Words Constrain On-Line Recognition of Verbs and Nouns in French 18-Month-Olds

2013

In this experiment using the conditioned head-turn procedure, 18-month-old French-learning toddlers were trained to respond to either a target noun (“la balle”/the ball) or a target verb (“je mange”/I eat). They were then tested on target word recognition in two syntactic contexts: the target word was preceded either by a correct function word (“une balle”/a ball or “on mange”/they eat), or by an incorrect function word, signaling a word from the other category (*“on balle”/they ball or *“une mange”/a eat). We showed that 18-month-olds exploit the syntactic context on-line to recognize the target word: verbs were recognized when preceded by a personal pronoun but not when preceded by a dete…

Linguistics and Languagebusiness.industryComputer scienceVerbcomputer.software_genreSyntaxLanguage and LinguisticsLinguisticsEducationCategorizationNounFunction wordWord recognitionPersonal pronounDeterminerArtificial intelligencebusinesscomputerNatural language processingLanguage Learning and Development
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Constructions-and-frames analysis of translations

2013

Translation can generally be seen as a task in which the meaning of the original should be preserved as far as possible. This paper formulates the preservation of meaning in terms of theprimacy of the framehypothesis: ideally, the frame of the original is matched by the frame of the translation. I investigate one factor overriding this principle in translations between English and German through the examination of two grammatical constructions, one in English, one in German, which are not commonly available in the other language. Picking a construction comparable in function in the target language leads to frame shifts. In addition to highlighting the interplay between construction and fram…

Linguistics and Languagebusiness.industryComputer sciencemedia_common.quotation_subjectcomputer.software_genreSemanticsLanguage and Linguisticslanguage.human_languageLinguisticsSyntax (logic)GermanMeaning (philosophy of language)Semantic similarityFactor (programming language)languageFrame (artificial intelligence)Artificial intelligencebusinessFunction (engineering)computerNatural language processingcomputer.programming_languagemedia_commonConstructions and Frames
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Optimal reciprocals in German Sign Language

2003

Unlike most spoken languages, German Sign Language (DGS) does not have a single means of reciprocal marking. Rather, different strategies are used, which crucially depend on phonological (one-handed sign vs. two-handed sign) and morphosyntactic (plain verb vs. agreement verb) properties of the underlying verb. Moreover, with plain verbs DGS shows dialectal variation. Altogether there are four different ways of realizing reciprocal marking in DGS. In this paper, we compare a rule-based analysis for the reciprocal data (based on Brentari’s 1998 feature hierarchy) to an optimality-theoretic analysis. We argue that an OT-account allows for a more straightforward explanation of the facts. In par…

Linguistics and Languagebusiness.industrymedia_common.quotation_subjectGerman Sign LanguageVerbOptimality theorySign languagecomputer.software_genreLanguage and Linguisticslanguage.human_languageAgreementLinguisticsVariation (linguistics)languageArtificial intelligencebusinesscomputerNatural language processingReciprocalmedia_commonSign (mathematics)Mathematics
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Discovering prominence and its role in language processing: an individual (differences) approach

2015

Abstract It has been suggested that, during real time language comprehension, the human language processing system attempts to identify the argument primarily responsible for the state of affairs (the “actor”) as quickly and unambiguously as possible. However, previous work on a prominence (e.g. animacy, definiteness, case marking) based heuristic for actor identification has suffered from underspecification of the relationship between different cue hierarchies. Qualitative work has yielded a partial ordering of many features (e.g. MacWhinney et al. 1984), but a precise quantification has remained elusive due to difficulties in exploring the full feature space in a particular language. Feat…

Linguistics and Languagecomputational modelactor identificationAmbiguity resolutionambiguity resolutionprominencelanguage processingemergencePsychologyindividual differencesLanguage and LinguisticsLinguistics
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Phrase Frames as an Exploratory Tool for Studying English-to-Polish Translation Patterns: A Descriptive Corpus-Based Study

2020

Designed as a proof-of-concept, this descriptive corpus-based study focuses on the concept of phrase frame, defined as a contiguous sequence of n words identical except for one (Fletcher 2002). Although phrase frames were already used as a means of exploring pattern variability across and within different text types or registers written in English, they have been rarely, if ever, employed so far as a unit of analysis in descriptive research on translation. In this study, we use the English‒Polish parallel corpus Paralela (Pęzik 2016) to identify and describe Polish translation patterns that emerge from two functionally-defined English phrase frames (it is * clear that, it is * difficult to ). …

Linguistics and Languagephrase framesPhraseComputer sciencebusiness.industryparallel corporaEnglish-to-Polish translationTranslation (geometry)computer.software_genreLanguage and LinguisticsphraseologyCorpus basedArtificial intelligencebusinesscorpus-based studycomputerNatural language processingAcross Languages and Cultures
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MLU and IPSyn measuring absolute complexity

2009

This article compares the results of Mean Length of Utterance (MLU) and Index of Productive Syntax (IPSyn) with the structural complexity of spontaneous utterances produced by 30-month-old Finnish children in a semi-structured playing situation. The comparison was carried out in order to determine the aspects of structural complexity which can be detected with MLU and IPSyn. This research adopts the frameworks of absolute complexity together with a multidimensional view of utterance structure and, furthermore, applies it through Utterance Analysis (UA). The results of the comparison between the metrics and changes in structural complexity discovered by UA reveal that MLU and IPSyn do functi…

Linguistics and Languagestructural complexitylcsh:Finnic. Baltic-Finniclcsh:PH91-98.5computer.software_genreLanguage and LinguisticsEducationStructural complexitylcsh:P1-1091child languageMathematicsStructure (mathematical logic)business.industryFinnishacquisitionFunction (mathematics)SyntaxFocus (linguistics)lcsh:Philology. LinguisticsIf and only ifArtificial intelligencebusinessMean length of utterancecomputerUtteranceNatural language processingmorphosyntaxEesti Rakenduslingvistika Ühingu aastaraamat. Estonian Papers in Applied Linguistics
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Semantic Word Error Rate for Sentence Similarity

2016

Sentence similarity measures have applications in several tasks, including: Machine Translation, Paraphrase Iden- tification, Speech Recognition, Question-answering and Text Summarization. However, measures designed for these tasks are aimed at assessing equivalence rather than resemblance, partly departing from human cognition of similarity. While this is reasonable for these activities, it hinders the applicability of sentence similarity measures to other tasks. We therefore propose a new sentence similarity measure specifically designed for resemblance evaluation, in order to cover these fields better. Experimental results are discussed.

Machine translationComputer scienceSpeech recognitionWord error rate02 engineering and technologycomputer.software_genreParaphrase030507 speech-language pathology & audiology03 medical and health sciencesSemantic similarityArtificial IntelligenceLSAWord Error Rate0202 electrical engineering electronic engineering information engineeringsentence resemblanceEquivalence (formal languages)Latent Semantic AnalysiSemantic Word Error Ratesentence similarity measureSWERbusiness.industryLatent semantic analysisSentence SimilaritySemantic ComputingCognitionAutomatic summarizationComputer Networks and Communicationword relatedne020201 artificial intelligence & image processingArtificial intelligence0305 other medical sciencebusinesscomputerNatural language processingWERInformation Systems2016 IEEE Tenth International Conference on Semantic Computing (ICSC)
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Robust Neural Machine Translation: Modeling Orthographic and Interpunctual Variation

2020

Neural machine translation systems typically are trained on curated corpora and break when faced with non-standard orthography or punctuation. Resilience to spelling mistakes and typos, however, is crucial as machine translation systems are used to translate texts of informal origins, such as chat conversations, social media posts and web pages. We propose a simple generative noise model to generate adversarial examples of ten different types. We use these to augment machine translation systems’ training data and show that, when tested on noisy data, systems trained using adversarial examples perform almost as well as when translating clean data, while baseline systems’ performance drops by…

Machine translationComputer sciencebusiness.industrycomputer.software_genreTranslation (geometry)Consistency (database systems)Robustness (computer science)Web pageNoise (video)Artificial intelligencebusinesscomputerSentenceOrthographyNatural language processing
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Source-Target Mapping Model of Streaming Data Flow for Machine Translation

2017

Streaming information flow allows identification of linguistic similarities between language pairs in real time as it relies on pattern recognition of grammar rules, semantics and pronunciation especially when analyzing so called international terms, syntax of the language family as well as tenses transitivity between the languages. Overall, it provides a backbone translation knowledge for building automatic translation system that facilitates processing any of various abstract entities which combine to specify underlying phonological, morphological, semantic and syntactic properties of linguistic forms and that act as the targets of linguistic rules and operations in a source language foll…

Machine translationDeep linguistic processingbusiness.industryComputer sciencepattern recognitiondata miningTransfer-based machine translationcomputer.software_genreSemanticsmachine translationUniversal Networking LanguageRule-based machine translationComputer-assisted translationstreaming data flowArtificial intelligenceLanguage familynatural language processingbusinesscomputerNatural language processing
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