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Common and distinct predictors of non-symbolic and symbolic ordinal number processing across the early primary school years
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Common and distinct predictors of non-symbolic and symbolic ordinal number processing across the early primary school years
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In: PLoS One (2021)
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Active Semi-Supervised Learning for Improving Word Alignment ...
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Active Semi-Supervised Learning for Improving Word Alignment ...
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Speech Recognition Challenge in the Wild: Arabic MGB-3 ...
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Abstract:
This paper describes the Arabic MGB-3 Challenge - Arabic Speech Recognition in the Wild. Unlike last year's Arabic MGB-2 Challenge, for which the recognition task was based on more than 1,200 hours broadcast TV news recordings from Aljazeera Arabic TV programs, MGB-3 emphasises dialectal Arabic using a multi-genre collection of Egyptian YouTube videos. Seven genres were used for the data collection: comedy, cooking, family/kids, fashion, drama, sports, and science (TEDx). A total of 16 hours of videos, split evenly across the different genres, were divided into adaptation, development and evaluation data sets. The Arabic MGB-Challenge comprised two tasks: A) Speech transcription, evaluated on the MGB-3 test set, along with the 10 hour MGB-2 test set to report progress on the MGB-2 evaluation; B) Arabic dialect identification, introduced this year in order to distinguish between four major Arabic dialects - Egyptian, Levantine, North African, Gulf, as well as Modern Standard Arabic. Two hours of audio per ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/1709.07276 https://dx.doi.org/10.48550/arxiv.1709.07276
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Challenging Language-Dependent Segmentation for Arabic: An Application to Machine Translation and Part-of-Speech Tagging ...
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The SUMMA Platform Prototype
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In: http://infoscience.epfl.ch/record/233575 (2017)
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The left intraparietal sulcus adapts to symbolic number in both the visual and auditory modalities: Evidence from fMRI
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In: Brain and Mind Institute Researchers' Publications (2017)
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Egyptian Arabic to English Statistical Machine Translation System for NIST OpenMT'2015 ...
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Enabling Medical Translation for Low-Resource Languages ...
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Nonparametric Word Segmentation for Machine Translation ...
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