The development of an automated method for analyzing communication rate in augmentative and alternative communication.

A significant barrier to evidence-based practice in Augmentative and Alternative Communication (AAC) is the lack of validated performance measures that can be used by speech-language pathologists and rehabilitation engineers to evaluate the communication and device use of AAC consumers. Recently an effort has been made to develop automated data-logging techniques to facilitate the transcription and analysis of the AAC speaker's device use. A major source of error for the automated measurement of communication rate is the presence of excessive Inter-Selection Intervals (ISIs) (i.e., pause times), for which no communicative activity is occurring. The goal of this study was to develop an automated technique to filter out extreme ISIs, while preserving true communication rate performance. AAC data log files were obtained from seven individuals participating in a 1-month field trial of an AAC technology. Two temporal filtering techniques (arbitrary and individual) were compared for their ability to eliminate excessive ISIs. Results indicated that use of an individualized temporal filter was more sensitive to performance variability than use of an arbitrary temporal filter. Further, the individualized temporal filter elevated the participants' communication rate (measured by words per minute) by a factor of 1.8 to 34.5 greater than that of the unfiltered communication rate estimate. In addition, the first AAC communication rate performance estimates taken from the field are presented. Implications for further research and the valid use of automated data logging and analysis are discussed.