Core Vocabulary
and the AAC Performance ReportKatya Hill, Ph.D., CCC-SLP
Barry Romich, P.E.
Core vocabulary is the relatively small number of words that constitute the vast majority of what is said in normal communication. With a few hundred words, a person can say over 80% of what is needed (Vanderheiden and Kelso, 1987). Extended, or fringe, vocabulary can be in the thousands or tens of thousands of words that are used infrequently, but constitute the remaining small portion of communication. Core vocabulary is generally consistent from one person to another, across ages, across environments, and across activities. Extended vocabulary is generally specific to particular environments and activities. Total communication requires the use of both core and extended vocabulary.For people who rely on AAC, appropriate use of core vocabulary is essential to effective communication (Yorkston, Dowden, Honsinger, Marriner, and Smith,1988; Fried-Oken and More, 1992) . If use of core vocabulary is low, communication effectiveness is likely to suffer. It is for this reason, that one of the quantitative summary measures of communication included in the AAC Performance Report is use of core vocabulary.
Another related issue is that the most effective communication results from the fastest and most automatic access to the most frequently used words (Hill and Romich, 2000). High frequency words have two components, general core vocabulary and personal core vocabulary. General core vocabulary consists of those words of high frequency that are of general conversational use. Examples of general core vocabulary words would be pronouns, articles, and prepositions. Personal core vocabulary consists of those words frequently used by a particular individual that are not frequently used by others. Examples of personal core vocabulary words would be names of people and places.
AAC professionals are careful to assure that high frequency words are located appropriately on the AAC system. Further, since access speed can be highly influenced by language representation methods, the fastest methods are used for the highest frequency words (Hill, Romich, Holko, 2001). One of the appendices of the AAC Performance Report is a frequency order listing of words used in the segmented utterances. This list can be a valuable resource in the planning, implementation, and evaluation of AAC intervention.
The AAC Performance Report includes both General Core Vocabulary and Personal Core Vocabulary measures. Each is reported as a percentage of the total number of spontaneously generated words included in the segmented utterances. Methods of calculation for frequency word lists have been documented and routinely used for databases (Tice and Beukelman, 1989; Miller and Chapman, 1991; Hill, 2001).
The general core vocabulary words are identified through checking for matches with a General Core Vocabulary (GCV) master list. The GCV list has been created based on a principled assessment of various vocabulary frequency studies. The list includes all morphological forms of high frequency general use words, even though all forms are not used with high frequency. The GCV master list is in a state of evolution and at the time of this writing has 440 words. The General Core Vocabulary list can be viewed at the AAC Institute web site under Products and Services / PeRT / Core Vocabulary and the AAC Performance Report. (Click here to view the list.) Suggestions of words that could be added to the list are welcome and should be sent to support@aacinstitute.org. Please include justification and evidence to support adding word(s) to the list.
PeRT (Performance Report Tool) software facilitates the generation of the AAC Performance Report from LAM (language activity monitoring) data. Individual words in the segmented utterances can be selected using a single click. The Word area of the PeRT screen allows words not in the GCV master list to be added to the Personal Core Vocabulary list for that individual. When a LAM file is opened using PeRT, the opportunity is provided to open the Personal Core Vocabulary file for that individual.
References
Fried-Oken, M., & More, L. (1992). An initial vocabulary for non-speaking preschool children based on developmental and environmental languaauge sources. Augmentative and Alternative Communication, 8, 41-56.
Hill, K. (2001). The development of a model for automated performance measurement and the establishment of performance indices for augmented communicators under two sampling conditions. Dissertation Abstracts International, 62(05), 2293. (UMI No. 3013368).
Hill, K., & Romich, B. (2000). AAC core vocabulary analysis: Tools for clinical use. In Proceedings of the RESNA 2000 Annual Conference. Orlando, FL: RESNA Press.
Miller, J. (1981). Assessing language production in children: Experimental procedures. Needham Heights, MA: Allyn and Bacon.
Miller, J. F., & Chapman, R.S. (1991). SALT: A computer program for the Systematic Analysis of Language Transcripts. Madison, WI: University of Wisconsin.
Tice, R., & Beukelman, D. (1989). Vocabulary frequency analyzer compare software (Research version 1.0). Department of Special Education and Communication Disorders, University of Nebraska, Lincoln, NE.
Vanderheiden, G. C., & Kelso, D. P. (1987). Comparative analysis of fixed-vocabulary communication acceleration techniques. AAC Augmentative and Alternative Communication, 3, 196-206.
Yorkston, K. M., Dowden, P. A., Honsinger, M. J., Marriner, N., & Smith, K. (1988). A comparison of standard and user vocabulary lists. AAC Augmentative and Alternative Communication, 4, 189-210.
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