Profet, a word prediction program, has been in use for the last ten years as a writing aid, and was designed to accelerate the writing process and minimize the writing effort for persons with motor dysfunction. It has also proved to be beneficial in spelling and text construction for persons with reading and writing difficulties due to linguistic impairments. With higher linguistic demands on support for individuals with severe reading and writing difficulties, including dyslexia, the need for an improved version of Profet has arisen. In this paper, the new functionality will be presented, and the possible implications for support at different linguistic levels will be discussed. Results from an evaluation study with individuals with motoric dysfunction and/or dyslexia will be presented at the workshop in Madrid. Word prediction systems h&ve existed since the early 1980s and were originally intended for the motoritally disabled but later also' for persons with linguistic impairments. Several different word prediction methods exist: Prediction can either be based on text statistics or linguistic rules. Some prediction programs also adapt to the user's language by using subject lexicons or learning modules. Among the first to develop word prediction programs for the PC were KTH with Predict (later Profet) (Hunnicutt, 1986 ) and ACSD with PAL (Swiffin et al, 1987 ) (Arnott et al, 1993 . Programs for the Macintosh include Co:Writer, which is distributed by Don Johnston, Inc. Profet is a statistically based adaptive word prediction program and is used as an aid in writing by individuals with motoric and/or linguistic disabilities, e.g., mild aphasia and dyslexia (Hunnicutt, 1986) , (Hunnicutt, 1989a). The program has undergone several stages of development at KTH since 1982 and runs on PC and Macintosh with Infovox and Monologue speech synthesis. It is used in Sweden (Profet) and Great Britain (Prophet) but is also being localized into Danish, Bokm~ (Norwegian), Dutch, Spanish, French, Russian, and Finnish. Upon typing at least one letter at the beginning of a word, the user is presented with a list of up to nine suggestions of likely word candidates. A word is chosen with the function key indicated to its right. However, if the intended word is not among the choices, the user can type the next letter of the target word, at which point he or she is presented with a new list of suggestions in the prediction window. Each time another letter is typed, a new list will be displayed, provided there is a match in the lexicon. A list of word suggestions is also presented after completion of a word, if that word is the first word in a pair in the bigram lexicon. However, when the user starts to type a new word, the predictor, being restricted to one information source at a time, solicits only the main lexicon, thus ignoring any previously typed word. The negative effect of this restriction is counterbalanced to a certain degree by the recency function, which, after each space and punctuation, records the word just completed. In this manner, a recently used word is promoted in the prediction list the next time the first letter(s) is/are typed. By selecting words in the prediction window, the motorically disabled user can economize keystrokes and physical energy. Similarly, the user who has difficulties spelling but is able to recognize the intended word in a list, is relieved of having to spell the whole word. However, the user who has problems with de-23
A statistical word prediction system, called Profet, was developed and used as a writing aid in Sweden REF .
Profet, A New Generation Of Word Prediction: An Evaluation Study
Workshop On Natural Language Processing For Communication Aids
Computer Science