PubMed · 2919705
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G D Erickson. 1989. Controlling auditory hallucinations.. https://doi.org/10.1176/ajp.146.3.aj1463406
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Assistive technology involving voice communication is used primarily by people who are deaf, hard of hearing, or who have speech and/or language disabilities. It is also used to a lesser extent by people with visual or motor disabilities. A very wide range of devices has been developed for people with hearing loss. These devices can be categorized not only by the modality of stimulation [i.e., auditory, visual, tactile, or direct electrical stimulation of the auditory nerve (auditory-neural)] but also in terms of the degree of speech processing that is used. At least four such categories can be distinguished: assistive devices (a) that are not designed specifically for speech, (b) that take the average characteristics of speech into account, (c) that process articulatory or phonetic characteristics of speech, and (d) that embody some degree of automatic speech recognition. Assistive devices for people with speech and/or language disabilities typically involve some form of speech synthesis or symbol generation for severe forms of language disability. Speech synthesis is also used in text-to-speech systems for sightless persons. Other applications of assistive technology involving voice communication include voice control of wheelchairs and other devices for people with mobility disabilities.
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Hue, saturation, and brightness were tested in pairs, with one dimension creating a classification context and the other serving as the basis of a set of speeded classification tasks. In Experiment 1, performance suffered when the context-setting dimension varied within a response category (intraclass context) and benefited when this variation occurred between response categories (redundant context). In Experiment 2, participants showed no interference from irrelevant variation in tasks that combined intraclass context with redundant context. Experiment 3 opened the interpretative window by varying 5 levels of intraclass context factorially with 5 levels of redundant context. The dimensions were found to differ in hardness--the degree of resistance to intraclass context across levels--with hue showing the greatest resistance and brightness the least. Hardness may reflect the efficacy of a dimension for distinguishing real-world categories.