What's Important in AAC?
The goal of AAC is the most effective communication possible.
The two most important values expressed by people who rely on AAC are:
1) saying exactly what they want to say, and
2) saying it as fast as they can.
Saying exactly the right thing requires spontaneous novel utterance generation (SNUG) (as opposed to the use of preprogrammed sentences). SNUG requires access to core vocabulary (those few hundred words that constitute the vast majority of communication) as well as to fringe vocabulary (the thousands of infrequently used words).
Communication speed, in words per minute, is a function of several factors. Perhaps the most significant factor is the language representation method(s) employed. Research based on subjects who rely on AAC has revealed that the communication rate using semantic compaction (Minspeak) can be up to six times that of spelling (Hill et.al., 2001).
Communication rate (words per minute) Frequency of Use (%)
SMP = Single Meaning Pictures; SPE = SPElling; WPR = Word PRediction; SEM = SEMantic compaction (Minspeak)
People who rely on AAC choose to use the fastest method for access to core vocabulary. Again, research based on those who rely on AAC has shown that they use semantic compaction for around 90% of communication. The remaining communication is split between spelling and word prediction (Hill, 2001) or single meaning pictures.
What gets the best results?
Speech-language pathologists and others providing services to people who rely on AAC have an ethical responsibility to take action that is in the best interests of the individual (ASHA, 2001). Evidence-based practice (EBP) is essential to get the best results. EBP requires the consideration of external evidence as well as collection and analysis of performance data on the individual being served.
AAC service providers must know and understand the way language is generated and the relative merits of the different methods (ASHA, 2002). Of the three language representation methods commonly used in AAC, research and clinical data clearly demonstrate that semantic compaction (Minspeak) not only allows SNUG but also can result in the fastest communication. Single meaning pictures and alphabet-based methods are generally better for extended vocabulary.
What is Minspeak?
Minspeak is a method of accessing language through the use of short sequences of multi-meaning icons (Baker, 1986). The power of Minspeak comes from a small symbol set (no changing overlays or screens), a short symbol sequence, and it does not require literacy skills. Here is an example of a statement using Minspeak.
I am hungry and I want something to eat
Anyone not familiar with the power of Minspeak may consider reading, attending a seminar, or taking a free Internet-based course. Information is available at www.prentrom.com. Minspeak represents patented intellectual property and as such is
supported only by specific AAC systems. All Prentke Romich Company AAC systems support Minspeak as well as the other language representation methods.
Results from various controlled studies indicate that learning Minspeak for functional communication is practical. Fluency using Minspeak can surpass that of spelling and word prediction within a few hours of instruction (Gardner-Boneau & Schwartz, 1989; Hill & Romich, 1999). Many fluent users of Minspeak received little or no professional support in learning their systems.
Minspeak is being used successfully by individuals with a wide range of language and intellectual capabilities. AAC professionals have reported use of Minspeak by individuals with IQ of 40 and above and also by young children (Watkins, 1996; Tullman & Hurtubise, 2000).
LAM and AAC Performance Measurement
AAC evidence-based clinical practice requires the collection and analysis of language samples. All AAC systems available from Prentke Romich Company have built-in language activity monitoring (LAM) to support evidence-based practice.
When activated, LAM records the content and time of language events. The following example shows the events that led to the utterance:
It's faster than spelling everything out which is what I used to do.
Analysis of language samples collected using the language activity monitor is used to guide therapy and measure outcomes.
References
American Speech-Language-Hearing Association (2001). Code of ethics (revised). Asha Leader, vol.6 (23), p. 2.
American Speech-Language-Hearing Association (2002). Augmentative and alternative communication: Knowledge and skills for service delivery. Rockville, Maryland. http://www.asha.org
Baker, B.R. (1986). Using images to generate speech. Byte, 11, 160-168.
Gardner-Bonneau, Daryle J., & Schwartz, Paul J. (1989). A Comparison of Words Strategy and Traditional Orthography.
In Proceedings of the 12th Annual RESNA Conference. pp. 286-287.
Hill, K.J. (2001). The development of a model for automated performance measurement and the establishment of performance indices for augmented communicators under two sampling conditions. Unpublished dissertation.
University of Pittsburgh, Pittsburgh, Pennsylvania.
Hill, K. & Romich, B. (1999). Identifying AAC Language Representation Methods Used by Persons with ALS. American Speech-Language-Hearing Association (ASHA) Convention, San Francisco.
Hill, K.J., Holko, R. & Romich, B. (2001). AAC Performance: The Elements of Communication Rate. American Speech- Language-Hearing Association (ASHA) Convention, New Orleans.
Tullman, J. & Hurtubise, C. (2000). Language activity monitoring on a young child using a VOCA. Proceedings of the Ninth Biennial Conference of ISAAC. pp. 310-313.
Watkins, C.W. (1996). Technology connection! Proceedings of the Tenth Minspeak Conference. Wooster, OH.
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