Effects of motifs in music therapy on the attention of children with externalizing behavior problems

Recent studies highlight the role of attention (i.e., executive attention and joint attention) in the negative association between children’s externalizing behavior problems (EBPs) and self-regulation. In music therapy improvisation, “Motifs” represent a repeated and meaningful use of freely improvised or structured music. They have been reported to be effective in drawing attention toward joint musical engagement. This study aimed to examine the effects of clinically derived motifs on the attention of a child with EBPs. Video microanalysis of four therapy sessions was employed. Interaction segments with/without motifs were then selected for analysis: (a) Executive attention measurement: a two-way analysis of variance (ANOVA) was conducted to examine the effects of Motifs (Factor I) across sessions (Factor II) on the duration of interaction segments. (b) Joint attention measurement: another two-way ANOVA investigated the effects of these two factors on the duration of joint attentive responses in each segment. Results showed that (a) the segments with Motifs tended to decrease in duration throughout the sessions, while (b) these segments showed a significant increase in proportions of joint attentional responses. These findings suggest a positive effect of Motifs on enhancing efficiency of joint attention execution over time, indicating the child’s recognition of the Motifs through learning

Development of the GALE 2008 Mandarin LVCSR System

This paper describes the current improvements of the RWTH Mandarin LVCSR system. We introduce vocal tract length normalization for the Gammatone features and present comparable results for Gammatone based feature extraction and classical feature extraction. In order to benefit from the huge amount of data of 1600h available in the GALE project we have trained the acoustic models up to 8M Gaussians. We present detailed character error rates for the different number of Gaussians. Different kinds of systems are developed and a two stage decoding framework is applied, which uses cross-adaptation and a subsequent lattice-based system combination. In addition to various acoustic front-ends, these systems use different kinds of neural network toneme posterior features. We present detailed recognition results of the development cycle and the different acoustic front-ends of the systems. Finally, we compare the ultimate evaluation system to our last years system and can report a 10 % relative improvement