Search results for "Test phase"

showing 2 items of 2 documents

Deep neural attention-based model for the evaluation of italian sentences complexity

2020

In this paper, the Automatic Text Complexity Evaluation problem is modeled as a binary classification task tackled by a Neural Network based system. It exploits Recurrent Neural Units and the Attention mechanism to measure the complexity of sentences written in the Italian language. An accurate test phase has been carried out, and the system has been compared with state-of-art tools that tackle the same problem. The computed performances proof the model suitability to evaluate sentence complexity improving the results achieved by other state-of-the-art systems.

050101 languages & linguisticsExploitComputer science02 engineering and technologyText complexity evaluationMachine learningcomputer.software_genreTask (project management)Text Simplification0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMeasure (data warehouse)Deep Neural NetworksArtificial neural networkSettore INF/01 - Informaticabusiness.industryItalian languageNatural language processing05 social sciencesComputer Science::Computation and Language (Computational Linguistics and Natural Language and Speech Processing)Deep learningText ComplexityBinary classification020201 artificial intelligence & image processingArtificial intelligenceTest phasebusinesscomputerSentence
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Hemispheric differences in specificity effects in talker identification

2010

In the visual domain, Marsolek and colleagues (1999, 2008) have found support for two dissociable and parallel neural subsystems underlying object and shape recognition: an abstract-category subsystem that operates more effectively in the left cerebral hemisphere (LH), and a specific-exemplar subsystem that operates more effectively in the right cerebral hemisphere (RH). Evidence of this asymmetry has been observed in priming specificity for linguistic (words, pseudoword forms) and nonlinguistic (objects) stimuli. In the auditory domain, the authors previously found hemispheric asymmetries in priming effects for linguistic (spoken words) and nonlinguistic (environmental sounds) stimuli. In …

Linguistics and Languagemedicine.medical_specialtyProperty (programming)Cervell--Localització de funcionsmedia_common.quotation_subjectObject (grammar)Experimental and Cognitive PsychologyAudiologyLanguage and LinguisticsPerceptionmedicineHumansDominance Cerebralmedia_commonCommunicationbusiness.industryHemisphere asymmetriesReconeixement de la parlaTalker identificationSensory SystemsSemanticsPseudowordAcoustic StimulationPattern Recognition VisualPrimingLateralitySpeech PerceptionTest phaseIdentification (psychology)Specificity effectsCuesPsychologybusinessPriming (psychology)Attention, Perception, & Psychophysics
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