This study examined the effect of written input on the production of word-final vowels (oral: /i/, /e/; nasal: /ɑ̃/, /ɔ̃/) by 100 native Moroccan learners of French as a second language, relying on a pretest/posttest paradigm. During pretest, participants performed a word repetition task. Then, participants were assigned to five experimental (training) conditions, varying in the modality of stimulus presentation (oral vs. written) and in the modality of response (oral vs. written), before their oral production of the word-final vowels was evaluated in the posttest. Results clearly showed that posttest pronunciation accuracy was affected by the presence of orthographic information in the training task. The copy training task was the most efficient at improving posttest accuracy. Results indicate that orthography, and more specifically the written production copy task, helps L2 learners’ pronunciation more efficiently than phonetic correction.
Adult studies in the fields of neurolinguistic and mental chronometry suggest that the syllable plays a functional role in handwritten word production. These studies support the hypothesis of a syllabified orthographic representation stored in the graphemic buffer. However, there remains the question of the cognitive mechanisms involved in this encoding of orthographic representations and, in particular, that of the processes related to the syllable. In the study reported here, we tested the hypothesis of an orthographic mental syllabary in long-term orthographic memory by exploring the impact of syllable frequency on handwritten latencies.Thirty participants handwrote the labels of one hundred and fifty images. Bayesian analyses indicated that the data support an absence of effect of syllable frequency. We propose an alternative hypothesis to the syllabary to account for the results in the literature. This respects the constraint of an absence of effect of syllable frequency in handwritten word production.
Fitting of the exponential modified Gaussian distribution to model reaction times and drawing conclusions from its estimated parameter values is one of the most popular method used in psychology. This paper aims to develop a Bayesian approach to estimate the parameters of the ex-Gaussian distribution. Since the chosen priors yield to posterior densities that are not of known form and that they are not always log-concave, we suggest to use the adaptive rejection Metropolis sampling method. Applications on simulated data and on real data are provided to compare this method to the standard maximum likelihood estimation method as well as the quantile maximum likelihood estimation. Results shows the effectiveness of the proposed Bayesian method by computing the root mean square error of the estimated parameters using the three methods.
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