Children's recall of words spoken in their first and second language : Effects of Signal-to-Noise Ratio and Reverberation Time

Speech perception runs smoothly and automatically when there is silence in the background, but when the speech signal is degraded by background noise or by reverberation, effortful cognitive processing is needed to compensate for the signal distortion. Previous research has typically investigated the effects of signal-to-noise ratio (SNR) and reverberation time in isolation, whilst few have looked at their interaction. In this study, we probed how reverberation time and SNR influence recall of words presented in participants' first- (L1) and second-language (L2). A total of 72 children (10 years old) participated in this study. The to-be-recalled wordlists were played back with two different reverberation times (0.3 and 1.2 s) crossed with two different SNRs (+3 dBA and +12 dBA). Children recalled fewer words when the spoken words were presented in L2 in comparison with recall of spoken words presented in L1. Words that were presented with a high SNR (+12 dBA) improved recall compared to a low SNR (+3 dBA). Reverberation time interacted with SNR to the effect that at +12 dB the shorter reverberation time improved recall, but at +3 dB it impaired recall. The effects of the physical sound variables (SNR and reverberation time) did not interact with language. © 2016 Hurtig, Keus van de Poll, Pekkola, Hygge, Ljung and Sörqvist.

The functions of Japanese Sound Symbolic Words in Different Types of Texts and Their Translation

Though sound symbolic words (onomatopoeia and mimetic words, or giongo and gitaigo in Japanese) exist in other languages, it would not be so easy to compare them to those in Japanese. This is because unlike in Japanese, in many other languages (here we see English and Spanish) sound symbolic words do not have distinctive forms that separate them immediately from the rest of categories of words. In Japanese, a sound symbolic word has a radical (that is based on the elaborated Japanese sound symbolic system), and often a suffix that shows subtle nuance. Together they give the word a distinctive form that differentiates it from other categories of words, though its grammatical functions could vary, especially in the case of mimetic words (gitaigo). Without such an obvious feature, in other languages, it would not be always easy to separate sound symbolic words from the rest. These expressions are extremely common and used in almost all types of text in Japanese, but their elaborated sound symbolic system and possibly their various grammatical functions are making giongo and gitaigo one of the most difficult challenges for the foreign students and translators. Studying the translation of these expressions into other languages might give some indication related to the comparison of Japanese sound symbolic words and those in other languages. Though sound symbolic words are present in many types of texts in Japanese, their functions in traditional forms of text (letters only) and manga (Japanese comics)are different and they should be treated separately. For example, in traditional types of text such as novels, the vast majority of the sound symbolic words used are mimetic words (gitaigo) and most of them are used as adverbs, whereas in manga, the majority of the sound symbolic words used (excluding those appear within the speech bubbles) are onomatopoeias (giongo) and often used on their own (i.e. not as a part of a sentence). Naturally, the techniques used to translate these expressions in the above two types of documents differ greatly. The presentation will focus on i) grammatical functions of Japanese sound symbolic words in traditional types of texts (novels/poems) and in manga works, and ii) whether their features and functions are maintained (i.e. whether they are translated as sound symbolic words) when translated into other languages (English and Spanish). The latter point should be related to a comparison of sound symbolic words in Japanese and other languages, which will be also discussed.

Genetic heterogeneity of residual variance : estimation of variance components using double hierarchical generalized linear models

Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used. Such models have previously been fitted using EM and MCMC algorithms. Results: We propose the use of double hierarchical generalized linear models (DHGLM), where the squared residuals are assumed to be gamma distributed and the residual variance is fitted using a generalized linear model. The algorithm iterates between two sets of mixed model equations, one on the level of observations and one on the level of variances. The method was validated using simulations and also by re-analyzing a data set on pig litter size that was previously analyzed using a Bayesian approach. The pig litter size data contained 10,060 records from 4,149 sows. The DHGLM was implemented using the ASReml software and the algorithm converged within three minutes on a Linux server. The estimates were similar to those previously obtained using Bayesian methodology, especially the variance components in the residual variance part of the model. Conclusions: We have shown that variance components in the residual variance part of a linear mixed model can be estimated using a DHGLM approach. The method enables analyses of animal models with large numbers of observations. An important future development of the DHGLM methodology is to include the genetic correlation between the random effects in the mean and residual variance parts of the model as a parameter of the DHGLM.