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      Templaticity Effects on Differential Processing of Consonants and Vowels

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          Abstract

          The aim of this study is to investigate the role of morphophonology and written representations in speech processing. Results are presented from an immediate serial recall (ISR) study, designed to determine the relative effects of L1 morphology and orthography on the recall of consonants versus vowels. Forty-five speakers of English, Amharic, and Arabic completed an ISR experiment testing the differential recall of these two segment types. English speakers remembered sequences of syllables in which the consonant is held constant and the vowel changes (e.g., “ma mi mu …”) better than sequences in which the vowel is held constant and the consonant changes (e.g., “ka ma za …”), whereas Arabic speakers remembered both types of sequences equally well, replicating findings from Kissling ( 2012). Crucially, Amharic speakers in this study performed similarly to Arabic speakers, remembering both sequence types with equal accuracy. Given that Amharic and Arabic share a templatic morphological system, this new result suggests that the morphophonology of a listener’s L1 impacts ISR. English and Amharic share similar orthographic systems; the mean accuracies of English and Amharic speakers were significantly different, and it therefore appears that orthography of the L1 does not affect recall accuracy. The results have implications for the role of the morphophonology of a given speaker’s L1 in ISR and in speech processing more generally.

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          Fitting Linear Mixed-Effects Models Using lme4

          Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer. Journal of Statistical Software, 67 (1) ISSN:1548-7660
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            Does awareness of speech as a sequence of phones arise spontaneously?

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              Learning at a distance I. Statistical learning of non-adjacent dependencies.

              In earlier work we have shown that adults, young children, and infants are capable of computing transitional probabilities among adjacent syllables in rapidly presented streams of speech, and of using these statistics to group adjacent syllables into word-like units. In the present experiments we ask whether adult learners are also capable of such computations when the only available patterns occur in non-adjacent elements. In the first experiment, we present streams of speech in which precisely the same kinds of syllable regularities occur as in our previous studies, except that the patterned relations among syllables occur between non-adjacent syllables (with an intervening syllable that is unrelated). Under these circumstances we do not obtain our previous results: learners are quite poor at acquiring regular relations among non-adjacent syllables, even when the patterns are objectively quite simple. In subsequent experiments we show that learners are, in contrast, quite capable of acquiring patterned relations among non-adjacent segments-both non-adjacent consonants (with an intervening vocalic segment that is unrelated) and non-adjacent vowels (with an intervening consonantal segment that is unrelated). Finally, we discuss why human learners display these strong differences in learning differing types of non-adjacent regularities, and we conclude by suggesting that these contrasts in learnability may account for why human languages display non-adjacent regularities of one type much more widely than non-adjacent regularities of the other type.

                Author and article information

                Contributors
                Journal
                1868-6354
                Laboratory Phonology: Journal of the Association for Laboratory Phonology
                Ubiquity Press
                1868-6354
                17 October 2019
                2019
                : 10
                : 1
                : 17
                Affiliations
                [1 ]Department of Linguistics, Georgetown University, Washington, DC, US
                Author information
                http://orcid.org/0000-0003-3374-3866
                Article
                10.5334/labphon.180
                c66d662d-df15-46f7-af9f-c45a796ca5f8
                Copyright: © 2019 The Author(s)

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.

                History
                : 14 November 2018
                : 23 September 2019
                Categories
                Journal article

                Applied linguistics,General linguistics,Linguistics & Semiotics
                Semitic linguistics,Phonological processing,Orthographic processing,Writing systems,Templatic morphology,Vowels,Consonants

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