The design principles of edutainment system for autistic children with communication difficulties

The number of children with autism is increasing worldwide. Children with autism face three major problems; socializing, communicating, and behaviour. Approximately 50% of all individuals with autism have difficulties in developing functional language owing to communication deterioration. Mobile devices with installed educational games help these individuals feel more comfortable and relaxed doing such activities. Although numerous mobile applications are available for individuals with autism, they are difficult to use; particularly in terms of user-interface design. This study analysed the existing apps in order to determine the design principles applicable to the Edutainment App being studied. Five applications were involved in this analysis. As outlined in the objectives of this study, identifying these design principles is important in designing the app. The analysis identified fifteen suggestions for the design principles. These suggestions addressed, simple interfaces; image size; number of pictures; home page icon; colour; having images identical to real life objects; the use of caregivers; navigation; password-protection; audio appropriate to the images; the app language used; evaluating parameters to measure the child’s growth; option for photo loading; PECS-based communication; and sentence pronunciation function. These recommendations are offered by this study towards designing and developing a prototype app for autistic children. This study introduces an edutainment-system design principle formulated to help develop the communication skills of children with autism-spectrum disorders. This study also describes the design, implementation, and evaluation of the ICanTalk app-a mobile edutainment app that can be used to improve users’ understanding and communication skills and help them to connect with society and the surrounding environment particularly for autistic children with communication difficulties. This app allows caregivers to create personalized content using pictures and audio on their mobile devices (tablets). The evaluation of the app by teachers suggests that it is useful and easy-to-use. In conclusion, based on the evaluation results, it is found that the ICanTalk app is effective in helping autistic children with communication difficultie

An Attention-Based Convolutional Recurrent Neural Networks for Scene Text Recognition

Text recognition is critical in various domains, including driving assistance, handwriting recognition, and aiding the visually impaired. In recent years, deep learning-based methods have demonstrated outstanding performance in Scene Text Recognition (STR). However, STR poses significant challenges, and the scarcity of non-Latin language datasets further compounds these challenges. To address this, we collected a dataset of Persian digits, including 20000 images with different challenges, making the dataset appropriate for text recognition task. Furthermore, we propose a convolutional-based model that incorporates the squeeze and excitation gate, forcing the model to focus on latent features, and connectionist temporal classification, enabling end-to-end sequence learning, for Persian digit recognition. We conduct extensive comparisons with different architectures and models to evaluate the performance of our proposed model. As a result, our approach achieves an accuracy of 94.26 on our datasets. The results demonstrate that our model outperforms the other methods, highlighting its effectiveness in Persian digit recognition