The use of cognitive-behavioural therapy (CBT) as a treatment for children and adolescents with autism spectrum disorder (ASD) has been explored in a number of trials. Whilst CBT appears superior to no treatment or treatment as usual, few studies have assessed CBT against a control group receiving an alternative therapy. Our randomised controlled trial compared use of CBT against person-centred counselling for anxiety in 36 young people with ASD, ages 12–18. Outcome measures included parent- teacher- and self-reports of anxiety and social disability. Whilst each therapy produced improvements in participants, neither therapy was superior to the other to a significant degree on any measure. This is consistent with findings for adults.

In this paper we have described the methodologies that we have used in data collection and recording for our Hindi Text to Speech system. Design of the speech corpus plays a very important role in overall quality of the text-to-speech system. A huge text corpus of one million words was created for existing text-to-speech system. We have crawled text from many domains like financial, government, current news etc. along with pre-built dictionaries. For the very first time, we have also generated and incorporated text from Hindi Short-Messaging-Service (SMS). The efforts were made to make the generic speech corpus for Hindi. The crawled text was first filtered for correctness e.g. spelling mistakes, validity to Hindi, word lengths etc. The filtered words were then carefully analyzed and ensured that phonetically balanced text is prepared. This cured text is then recorded by professional recordist in a studio environment. The recorded speech data is then processed and annotated to generate the final speech corpus. The paper explains the speech corpus creation process, beginning with text data crawling, filtering, recording and annotation phases. The final speech corpus thus generated is used in the Hindi Text-to-Speech system with the MOS of 2.8.

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Major depressive disorder (MDD) affects at some point in their lives a tenth of the world's population with a higher incidence in females than males. Like all clinical disorders encountered in adult psychiatry, a diagnosis of MDD is symptom-based and has not been externally validated. Eye movement dysfunctions (EMDs) in the functional psychoses have been extensively reported and their potential as biomarkers highlighted but it is unclear whether there are patterns of EMDs specific to MDD. Abnormal EMs in bipolar affective cases have been observed during face and picture viewing, saccadic control and smooth pursuit tasks. However most studies reporting EMs in affective disorders, have not distinguished between unipolar/MDD and bipolar cases. to address this problem we have compared performance on a broad range of EM tests in patients meeting DSM-IV criteria for MDD with identical measures made in a large sample of bipolar, schizophrenia and undiagnosed individuals. Remarkably a network classifier was able to delineate controls and each patient group using EM performance measures with exceptional sensitivity (94%) and specificity (98%). What is more, probability of illness category was not associated with demographic, symptom, neuropsychological or medication variables. It therefore appears that a unique multivariate eye movement phenotype may be associated with MDD. If verified in further MDD cases these findings could be an enormous advance in helping to assess and/or diagnose individuals with symptoms of MDD or at risk of developing MDD.