Telling tales: unlocking the potential of AAC technologies

Waller, Annalu

doi:10.1111/1460-6984.12449

Cited by 50 publications

(49 citation statements)

References 48 publications

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“…A recent study [87] similarly reported that most BCI technologies still offer conversational rates of less than 20 letters per minute. Generally, the rates of conversation using AAC systems, including word prediction and letter abbreviation, were found to be between 12-18 WPM, highly contrasting with the rates of natural speech [93]. • IR is invisible to the user's eyes [23] • IR can stabilize gaze estimation [23] • High Temporal resolution = high volume of data as patterns are averaged over long time spans [90]; Consequence: sample sizes are often small [91] • Eye tracking data processing [91] and parsing is complex [90] • Need for calibration algorithms • IR signals are not reliable for outdoor use [23] • Generally, high cost [27] Head-pointing…”

Section: Conversational Ratesmentioning

confidence: 96%

“…Natural speech has a rate of 125 to 185 words per minute (WPM) [93]. Speech rates of less than 100 WPM are identified as slow [94].…”

Section: Conversational Ratesmentioning

confidence: 99%

“…Speech rates of less than 100 WPM are identified as slow [94]. Direct selection techniques, including eye gaze systems, are found to provide conversational rates of about 8-10 WPM [93]. Likewise, mechanically activated AAC switches and keyboards also affect the conversational rates.…”

Section: Conversational Ratesmentioning

confidence: 99%

“…The automatic, step, and inverse activation of switches often requires the users to wait until the desired selection is displayed, introducing conversational delays. Scanning methods were reported to allow communicative rates of around two WPM [93]. Selecting letters to form words may also impact the user's communication rate.…”

Section: Conversational Ratesmentioning

confidence: 99%

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Augmentative and Alternative Communication (AAC) Advances: A Review of Configurations for Speech Disabled Individuals

Elsahar¹,

Hu²,

Bouazza-Marouf³

et al. 2019

Preprint

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High-tech augmentative and alternative communication (AAC) methods are on a constant rise; however, the interaction between the user and the assistive technology is still challenged for an optimal user experience centered around the desired activity. This review presents a range of signal sensing and acquisition methods utilized in conjunction with the existing high-tech AAC platforms for speech disabled individuals, including imaging methods, touch-enabled systems, mechanical and electro-mechanical access, breath-activated methods, and brain computer interfaces (BCI). The listed AAC sensing modalities are compared in terms of ease of access, affordability, complexity, portability, and typical conversational speeds. A revelation of the associated AAC signal processing, encoding, and retrieval highlights the roles of machine learning (ML) and deep learning (DL) in the development of intelligent AAC solutions. The demands and the affordability of most systems were found to hinder the scale of usage of high-tech AAC. Further research is indeed needed for the development of intelligent AAC applications reducing the associated costs and enhancing the portability of the solutions for a real user’s environment. The consolidation of natural language processing with current solutions also needs to be further explored for the amelioration of the conversational speeds. The recommendations for prospective advances in coming high-tech AAC are addressed in terms of developments to support mobile health communicative applications.

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Section: Conversational Ratesmentioning

confidence: 96%

“…Natural speech has a rate of 125 to 185 words per minute (WPM) [93]. Speech rates of less than 100 WPM are identified as slow [94].…”

Section: Conversational Ratesmentioning

confidence: 99%

Section: Conversational Ratesmentioning

confidence: 99%

Section: Conversational Ratesmentioning

confidence: 99%

See 2 more Smart Citations

Augmentative and Alternative Communication (AAC) Advances: A Review of Configurations for Speech Disabled Individuals

Elsahar¹,

Hu²,

Bouazza-Marouf³

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…AAC offers communication support through systems that are unaided or aided (ASHA ). Unaided systems require no technology (e.g., gestures), while aided systems comprise of non‐electronic, paper‐based solutions (e.g., memory books) or electronic, highly technologically dependent devices (e.g., computer technology) (Waller ).…”

Section: Introductionmentioning

confidence: 99%

Review of AAC interventions in persons with dementia

May

Dada

Murray

2019

Intl J Lang & Comm Disor

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Background: Communication is an important priority in dementia research. Communication strategies and scaffolds, specifically through augmentative and alternative communication (AAC), offer vital compensatory support for persons with dementia in an attempt to maintain the latter's quality of life and well-being through participation with others. To date, no research review has been published that synthesizes the current research of AAC in the field of dementia. Aims: To provide an overview of current AAC strategies and techniques used for supporting communication in dementia by surveying the literature base in a systematic manner, synthesizing the findings and highlighting trends and gaps. Methods & Procedures:A multifaceted search strategy included nine electronic database searches, using specific keywords. Application of predefined selection criteria during screening procedures led to the inclusion of 39 studies. Data were extracted and studies synthesized according to communication partners; description of AAC strategies and techniques; outcome measures; and communication outcomes.Main Contribution: This review shows that the majority of the research to date has focused on supporting the interactions of persons with dementia of the Alzheimer's type (DAT) using non-electronic memory and communication aids. Future research should focus on social participation and person-centred communication to optimize functional communication with AAC. Training programmes targeting dyadic interaction and supporting persons with dementia from diverse ethnic backgrounds are avenues for further research. Conclusions: Research trends and, more importantly, the gaps highlighted in this research review present speechlanguage therapists and researchers with a set of current priorities that are necessary for the advancement of the knowledge base. What this paper addsWhat is already known on the subject Communication strategies and scaffolds, specifically through AAC, are known to offer vital compensatory support for persons with dementia. Studies of AAC in dementia are scattered across previous reviews based on the focus and scope of each enquiry. No current reviews exist that have specifically focused on supporting dementia-related communication with AAC. As such, a more systematic approach to synthesize the current knowledge base is required. What this paper adds to existing knowledgeThis research review is the first to search the literature systematically: first, to locate studies focused on AAC that are used to support communication in persons with dementia; and second, to synthesize the findings obtained. 858Auriel A. May et al. What are the potential or actual clinical implications of this work?This review makes a unique contribution to the field of dementia by presenting researchers with a set of current priorities that are necessary for the advancement of the knowledge base.

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AI and Global AAC Symbol Communication

Ding

Draffan

Wald

2020

Lecture Notes in Computer Science

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Artificial Intelligence (AI) applications are usually built on large trained data models that can recognize and label images, provide speech output from text, process natural language for translation, and be of assistance to many individuals via the internet. For those who are non-verbal or have complex speech and language difficulties, AI has the potential to offer enhanced access to the wider world of communication that can be personalized to suit user needs. Examples include pictographic symbols to augment or provide an alternative to spoken language. However, when using AI models, data related to the use of freely available symbol sets is scarce. Moreover, the manipulation of the data available is difficult with limited annotation, making semantic and syntactic predictions and classification a challenge in multilingual situations. Harmonization between symbol sets has been hard to achieve; this paper aims to illustrate how AI can be used to improve the situation. The goal is to provide an improved automated mapping system between various symbol sets, with the potential to enhance access to more culturally sensitive multilingual symbols. Ultimately, it is hoped that the results can be used for better context sensitive symbol to text or text to symbol translations for speech generating devices and web content.

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Telling tales: unlocking the potential of AAC technologies

Cited by 50 publications

References 48 publications

Augmentative and Alternative Communication (AAC) Advances: A Review of Configurations for Speech Disabled Individuals

Augmentative and Alternative Communication (AAC) Advances: A Review of Configurations for Speech Disabled Individuals

Review of AAC interventions in persons with dementia

AI and Global AAC Symbol Communication

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