Comparing Interventions With Speech-Generating Devices and Other Augmentative and Alternative Communication Modes: A Meta-Analysis

Pak, Natalie S.; Bailey, Kathryn; Ledford, Jennifer R.; Kaiser, Ann P.

doi:10.1044/2022_ajslp-22-00220

Cited by 2 publications

(1 citation statement)

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“…Set of pictures or symbols can be used to communicate to non-verbal individuals after appropriate training. One of the most common aided AAC interventions to enhance functional communication skills is the Picture Exchange Communication System (Bondy and Frost, 1994), which is used for example with children affected by autistic spectrum disorder (ASD) (Pak et al, 2023). First, users learn to communicate with one picture symbol by associating the picture with desired token (e.g., some pretzels) and then learn to select between two or more pictures.…”

Section: Introductionmentioning

confidence: 99%

Validation of a pictionary-based communication tool for assessing physiological needs and motivational states: the PAIN set

Proverbio

Pischedda

2023

Front. Cognit.

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This Pictionary is suitable for communicating with individual unable to interact (locked-in syndrome, LIS) through the development of Brain Computer Interface (BCI) systems. It includes 60 validated, easy-to-understand illustrated plates depicting adults in various situations affecting their physiological or psychological state. The drawings are in color and represent persons of both sexes and various ethnicities. Twenty participants were interviewed to appropriately design the Pictionary. An additional group of 50 healthy adults (25 women and 25 men) aging 18–33 years was recruited to validate the pictogram corpus. Their schooling levels ranged from middle school to master's degrees. Participants were presented with five runs of randomly mixed pictograms illustrating 12 different motivational states, including primary and secondary needs, affective states, and somatosensory sensations (with five variants for each category). They had to precisely identify the motivational category illustrated (e.g., “Feeling pain” or “Being hungry”) while also providing information about its clarity and unambiguity on a Likert scale. Statistical analyses provided evidence of the strong communicative effectiveness of the illustrations (rated on average 2.7, on a 0 to 3 scale), with an accuracy of 98.4%. The PAIN set could be a valuable communication tool for individuals with LIS, as well as any clinical population lacking verbal communication skills. Its main purpose is to generate electrophysiological markers of internal mental states to be automatically classified by BCI systems.

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Section: Introductionmentioning

confidence: 99%

Validation of a pictionary-based communication tool for assessing physiological needs and motivational states: the PAIN set

Proverbio

Pischedda

2023

Front. Cognit.

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AI-Generated Images for Speech Pathology—An Exploratory Application to Aphasia Assessment and Intervention Materials

Pierce

2024

Am J Speech Lang Pathol

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Purpose: Images are a core component of aphasia assessment and intervention that require significant resources to produce or source. Text-to-image generation is an Artificial Intelligence (AI) technology that has recently made significant advances and could be a source of low-cost, highly customizable images. The aim of this study was to explore the potential of AI image generation for use in aphasia by examining its efficiency and cost during generation of typical images. Method: Two hundred targets (80 nouns, 80 verbs, and 40 sentences) were selected at random from existing aphasia assessments and treatment software. A widely known image generator, DALL-E 2, was given text prompts for each target. The success rate, number of prompts required, and costs were summarized across target categories (noun/verb/sentence) and compared to frequency and imageability. Results: Of 200 targets, 189 (94.5%) successfully conveyed the key concept. The process took a mean of 2.3 min per target at a cost of $0.31 in U.S. dollars each. However, there were aesthetic flaws in many successful images that could impact their utility. Noun images were generated with the highest efficiency and accuracy, followed by verbs, while sentences were more challenging, particularly those with unusual scenes. Patterns of flaws and errors in image generation are discussed. Conclusion: The ability to rapidly generate low-cost, high-quality images using AI is likely to be a major contribution to aphasia assessment and treatment going forward, particularly as advances in this technology continue.

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Comparing Interventions With Speech-Generating Devices and Other Augmentative and Alternative Communication Modes: A Meta-Analysis

Cited by 2 publications

References 51 publications

Validation of a pictionary-based communication tool for assessing physiological needs and motivational states: the PAIN set

Validation of a pictionary-based communication tool for assessing physiological needs and motivational states: the PAIN set

AI-Generated Images for Speech Pathology—An Exploratory Application to Aphasia Assessment and Intervention Materials

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