No abstract

This work investigates the production of Italian dental affricates /ts dz/ by Irish English learners at the National University of Ireland, Galway. Dental affricates are sounds that are difficult for non-native speakers to acquire, and they vary greatly across Italian dialects. Previous works on the topic have demonstrated that learners tend to reduce affricates to fricatives, and that the voiced /dz/ is often substituted with the voiceless in every context. This survey investigates the production of 7 speakers divided into A2 and B1 levels.Participants were asked to compile a background questionnaire and to read a list of 47 sentences containing 52 dental affricates in different phonological contexts. Phonetic annotation was manually conducted on PRAAT, and the analysis focused on durational cues and realization of voicing. The results showed that voiced affricates were rarely produced and were often substituted with their voiceless counterpart, thus leading to the general non-acquisition of voicing for this class of phoneme. Furthermore, the length of the occlusive segment was shorter than the fricative one, particularly in the post-sonorant context; a gap between the occlusive and fricative portion has also been detected. No substantial differences between the A2 and B1 levels emerged.

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis that can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling but also from decisions regarding the quantification of the measured behavior. In this study, we gave the same speech-production data set to 46 teams of researchers and asked them to answer the same research question, resulting in substantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further found little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise, or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system, and calibrate their (un)certainty in their conclusions.