As the size of the stored information corpus in an AAC system increases, the task of searching and retrieving items from that corpus will become more demanding, which will make it less easy for someone to successfully access and use such material. Computer-based AAC systems can contain stored communication material for people with impaired communication to retrieve and use during interaction. AAC systems exist to assist people to overcome communication handicaps. This study investigated the possibility of using Information Visualisation (IV) in the user interface of Augmentative and Alternative Communication (AAC) systems. This insight will potentially enable the development of new applications for speech therapy, the quantization and visualization of vocal trends common to speakers with medical conditions such as autism spectrum disorder (ASD), the characterization and visualization of communication patterns common in different kinds of relationships and cultures, and the development of new kinds of creative, multimodal works. By making the overlooked channels of human communication visible and persistent, we make it possible to see beneath the surface of our words. In this paper, we describe a voice analytics toolkit and present visualizations that focus on the relational and expressive verbal gestures in speech. Even though we are able to record sound and play it back, we typically focus more on the semantic meaning of words. Furthermore, sound in human communication is multidimensional and includes the semantic meaning of words, the meaning of expressive verbal gestures (paralingual and prosodic components), the nonvocal gestures, and relational gestures. We experience it as it happens, often in community with others. Sound has been an overlooked modality in visualization. Informed by these findings, we propose a possible future research agenda and offer suggestions for the features of successful collaboration to guide the design of advanced affordances. At the same time, existing visual analysis approaches have mainly targeted learners or researchers and mainly focused on mirroring collaborative discourse rather than providing advanced affordances such as alerting or advising. However, it has been challenging for current research to simultaneously consider learning theories and follow visualisation design principles when adopting visualisations to analyse collaborative discourse. We found visual analysis approaches to be suitable and advantageous for decomposing the temporality of collaborative discourse. This review uses the lens of visual analytics to examine four dimensions of visual representations of collaborative discourse: goals, data sources, visualisation designs, and analytical techniques. ICQ 2003b Download Now Released: Add info Size: 4.Visual analytics combines automated data analysis and human intelligence through visualisation techniques to address the complexity of current real-world problems.
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