Assistive Technologies Research: Communication Disabilities

Automatic speech recognition and training for severely dysarthric users of assistive technology: the STARDUST project.

Parker M, Cunningham S, Enderby P, Hawley M, Green P.  Sheffield Speech and Language Therapy Agency, Sheffield, UK.  Clin Linguist Phon. 2006 Apr-May;20(2-3):149-56.

The STARDUST project developed robust computer speech recognizers for use by eight people with severe dysarthria and concomitant physical disability to access assistive technologies. Independent computer speech recognizers trained with normal speech are of limited functional use by those with severe dysarthria due to limited and inconsistent proximity to “normal” articulatory patterns. Severe dysarthric output may also be characterized by a small mass of distinguishable phonetic tokens making the acoustic differentiation of target words difficult. Speaker dependent computer speech recognition using Hidden Markov Models was achieved by the identification of robust phonetic elements within the individual speaker output patterns. A new system of speech training using computer generated visual and auditory feedback reduced the inconsistent production of key phonetic tokens over time.

Prescribing assistive-technology systems: focus on children with impaired communication.

Desch LW, Gaebler-Spira D; Council on Children With Disabilities.  Collaborators (12)   Murphy NA, Cartwright JD, Desch LW, Duby JC, Elias ER, Liptak GS, Myers SM, Norwood KW Jr, Sagerman PJ, Tilton AH, Lipkin PH, Gaebler-Spira DPediatrics. 2008 Jun;121(6):1271-80.

This clinical report defines common terms of use and provides information on current practice, research, and limitations of assistive technology that can be used in systems for communication. The assessment process to determine the best devices for use with a particular child (ie, the best fit of a device) is also reviewed. The primary care pediatrician, as part of the medical home, plays an important role in the interdisciplinary effort to provide appropriate assistive technology and may be asked to make a referral for assessment or prescribe a particular device. This report provides resources to assist pediatricians in this role and reviews the interdisciplinary team functional evaluation using standardized assessments; the multiple funding opportunities available for obtaining devices and ways in which pediatricians can assist families with obtaining them; the training necessary to use these systems once the devices are procured; the follow-up evaluation to ensure that the systems are meeting their goals; and the leadership skills needed to advocate for this technology. The American Academy of Pediatrics acknowledges the need for key resources to be identified in the community and recognizes that these resources are a shared medical, educational, therapeutic, and family responsibility. Although this report primarily deals with assistive technology specific for communication impairments, many of the details in this report also can aid in the acquisition and use of other types of assistive technology.


A speech-controlled environmental control system for people with severe dysarthria.

Hawley MS, Enderby P, Green P, Cunningham S, Brownsell S, Carmichael J, Parker M, Hatzis A, O’Neill P, Palmer R.  Department of Medical Physics and Clinical Engineering, Barnsley Hospital NHS Foundation Trust, UK.  Med Eng Phys. 2007 Jun;29(5):586-93. Epub 2006 Oct 17.

Automatic speech recognition (ASR) can provide a rapid means of controlling electronic assistive technology. Off-the-shelf ASR systems function poorly for users with severe dysarthria because of the increased variability of their articulations. We have developed a limited vocabulary speaker dependent speech recognition application which has greater tolerance to variability of speech, coupled with a computerised training package which assists dysarthric speakers to improve the consistency of their vocalisations and provides more data for recogniser training. These applications, and their implementation as the interface for a speech-controlled environmental control system (ECS), are described. The results of field trials to evaluate the training program and the speech-controlled ECS are presented. The user-training phase increased the recognition rate from 88.5% to 95.4% (p<0.001). Recognition rates were good for people with even the most severe dysarthria in everyday usage in the home (mean word recognition rate 86.9%). Speech-controlled ECS were less accurate (mean task completion accuracy 78.6% versus 94.8%) but were faster to use than switch-scanning systems, even taking into account the need to repeat unsuccessful operations (mean task completion time 7.7s versus 16.9s, p<0.001). It is concluded that a speech-controlled ECS is a viable alternative to switch-scanning systems for some people with severe dysarthria and would lead, in many cases, to more efficient control of the home.


Speech recognition software as an assistive device: a pilot study of user satisfaction and psychosocial impact.

Derosier R, Farber RS.  Polisher Research Institute, Madlyn and Leonard Abramson Center for Jewish Life, 1425 Horsham Road, North Wales, PA 19454, USA.  Work. 2005;25(2):125-34.

The purpose of this study was to gather data concerning the psychosocial (quality of life) impact of speech recognition software on individuals with physical disabilities and to identify how satisfied these individuals were with this software as a computer access method. Two standardized questionnaires, the Psychosocial Impact of Assistive Devices Scale (PIADS) and the Quebec User Evaluation of Satisfaction with assistive Technology (QUEST) were administered to ten participants with physical disabilities who received speech recognition software following an assistive technology evaluation. The results of this study indicated that 90% of the participants were quite satisfied with speech recognition software as an assistive device and that the software had a somewhat positive psychosocial impact on their lives. Four themes emerged concerning what the participants liked most about the software: 1) the software provided a method of access when they were not previously accessing a computer, 2) the software increased independence, 3) the software made computer use more efficient, and 4) the software provided a choice or flexibility in computer access. Although this study demonstrated that these speech recognition software users are generally satisfied with the software and it has had a positive impact on their life, it also suggests that there is a need to examine the role of training on satisfaction and successful use of the software.