Huffman and Linear Scanning Methods with Statistical Language Models

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TitleHuffman and Linear Scanning Methods with Statistical Language Models
Publication TypeJournal Article
AbstractCurrent scanning access methods for text generation in AAC devices are limited to relatively few options, most notably row/column variations within a matrix. We present Huffman scanning, a new method for applying statistical language models to binary-switch, static-grid typing AAC interfaces, and compare it to other scanning options under a variety of conditions. We present results for 16 adults without disabilities and one 36-year-old man with locked-in syndrome who presents with complex communication needs and uses AAC scanning devices for writing. Huffman scanning with a statistical language model yielded significant typing speedups for the 16 participants without disabilities versus any of the other methods tested, including two row/column scanning methods. A similar pattern of results was found with the individual with locked-in syndrome. Interestingly, faster typing speeds were obtained with Huffman scanning using a more leisurely scan rate than relatively fast individually calibrated scan rates. Overall, the results reported here demonstrate great promise for the usability of Huffman scanning as a faster alternative to row/column scanning.
AuthorsRoark, B., Fried-Oken M., and Gibbons C.
Year of Publication2015
PublicationJournal of Augmentative and Alternative Communication
ISSN0743-4618 (print), 1477-3848 (online)
Publisher DOI
Keywords (MeSH)adult, communication aids for disabled, language, software