Is Swedish more beautiful than Danish? Matched guise investigations with unknown languages

Are some languages universally seen as beautiful? And if so, what are the linguistic traits that make some languages sound more pleasing than others? This paper addresses these two questions. We do so with results from two listener experiments that use speech samples from a bilingual Danish–Swedish speaker in a matched guise test, where the listeners are ‘previously unexposed’ students from central China. Our results indicate that listeners from Central China with no previous exposure find Swedish more pleasing sounding than Danish. This finding provides evidence that there could be features of language that sound more beautiful to listeners cross-culturally. In a follow-up experiment we remove the intonation contours of the speech to see whether this prosodic trait plays a role for evaluations. The results show that the difference in evaluations between Swedish and Danish disappears when both speech samples are monotonised. We discuss the importance of our findings for language attitudes research

Predicting mutual intelligibility among Chinese dialects from subjective and objective linguistic similarity measures

We determined subjective mutual intelligibility and linguistic similarity by presenting recordings of the same spoken passage in 15 Chinese dialects to naive listeners of the same set of dialects and asking them to rate the dialects along both subjective dimensions. We then regressed the subjective ratings against objective structural similarity measures (lexical, phonological) for the same set of dialects as published in the literature. Our results show that subjective distance is better predicted than subjective mutual intelligibility and that the relationship between objective and subjective measures is logarithmic. Best predicted was log-transformed subjective similarity (excluding the Beijing dialect, which is identical to the standard language) with R2 = .64

Identifying suitable reference genes for gene expression analysis in developing skeletal muscle in pigs

The selection of suitable reference genes is crucial to accurately evaluate and normalize the relative expression level of target genes for gene function analysis. However, commonly used reference genes have variable expression levels in developing skeletal muscle. There are few reports that systematically evaluate the expression stability of reference genes across prenatal and postnatal developing skeletal muscle in mammals. Here, we used quantitative PCR to examine the expression levels of 15 candidate reference genes (ACTB, GAPDH, RNF7, RHOA, RPS18, RPL32, PPIA, H3F3, API5, B2M, AP1S1, DRAP1, TBP, WSB, and VAPB) in porcine skeletal muscle at 26 different developmental stages (15 prenatal and 11 postnatal periods). We evaluated gene expression stability using the computer algorithms geNorm, NormFinder, and BestKeeper. Our results indicated that GAPDH and ACTB had the greatest variability among the candidate genes across prenatal and postnatal stages of skeletal muscle development. RPS18, API5, and VAPB had stable expression levels in prenatal stages, whereas API5, RPS18, RPL32, and H3F3 had stable expression levels in postnatal stages. API5 and H3F3 expression levels had the greatest stability in all tested prenatal and postnatal stages, and were the most appropriate reference genes for gene expression normalization in developing skeletal muscle. Our data provide valuable information for gene expression analysis during different stages of skeletal muscle development in mammals. This information can provide a valuable guide for the analysis of human diseases