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Variation in the speech signal as a window into the cognitive architecture of language production
(2018)
The pronunciation of words is highly variable. This variation provides crucial information about the cognitive architecture of the language production system. This review summarizes key empirical findings about variation phenomena, integrating corpus, acoustic, articulatory, and chronometric data from phonetic and psycholinguistic studies. It examines how these data constrain our current understanding of word production processes and highlights major challenges and open issues that should be addressed in future research.
In connected speech, many words are produced with a pronunciation that differs from the canonical form. How the speech recognition system deals with this variation is a fundamental issue in the language processing literature. The present study examines the roles of variant type, variant frequency, and context in the processing of French words with a canonical (schwa variant, e.g. semaine “week”) and a non-canonical pronunciation (no-schwa variant, s’maine). It asks whether the processing of canonical pronunciations is faster than the processing of non-canonical ones. Results of three lexical decision experiments reveal that more frequent variants are recognised more quickly, and that there is no advantage for canonical forms once variant frequency is accounted for. Two of these experiments further failed to find evidence that the context in which the words are presented modulate the effect of variant type. These findings are discussed in the light of spoken word recognition models.
This study examines the influence of orthography on the processing of reduced word forms. For this purpose, we compared the impact of phonological variation with the impact of spelling-sound consistency on the processing of words that may be produced with or without the vowel schwa. Participants learnt novel French words in which the vowel schwa was present or absent in the first syllable. In Experiment 1, the words were consistently produced without schwa or produced in a variable manner (i.e., sometimes produced with and sometimes produced without schwa). In Experiment 2, words were always produced in a consistent manner, but an orthographic exposure phase was included in which words that were produced without schwa were either spelled with or without the letter < e >. Results from naming and eye-tracking tasks suggest that both phonological variation and spelling-sound consistency influence the processing of spoken novel words. However, the influence of phonological variation outweighs the effect of spelling-sound consistency. Our findings therefore suggest that the influence of orthography on the processing of reduced word forms is relatively small.
Background: Event-related potentials (ERPs) are increasingly used in cognitive science. With their high temporal resolution, they offer a unique window into cognitive processes and their time course. In this paper, we focus on ERP experiments whose designs involve selecting participants and stimuli amongst many. Recently, Westfall et al. (2017) highlighted the drastic consequences of not considering stimuli as a random variable in fMRI studies with such designs. Most ERP studies in cognitive psychology suffer from the same drawback. New method: We advocate the use of the Quasi-F or Mixed-effects models instead of the classical ANOVA/by-participant F1 statistic to analyze ERP datasets in which the dependent variable is reduced to one measure per trial (e.g., mean amplitude). We combine Quasi-F statistic and cluster mass tests to analyze datasets with multiple measures per trial. Doing so allows us to treat stimulus as a random variable while correcting for multiple comparisons. Results: Simulations show that the use of Quasi-F statistics with cluster mass tests allows maintaining the family wise error rates close to the nominal alpha level of 0.05. Comparison with existing methods: Simulations reveal that the classical ANOVA/F1 approach has an alarming FWER, demonstrating the superiority of models that treat both participant and stimulus as random variables, like the Quasi-F approach. Conclusions: Our simulations question the validity of studies in which stimulus is not treated as a random variable. Failure to change the current standards feeds the replicability crisis.