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AI and global AAC symbol communication

AI and global AAC symbol communication
AI and global AAC symbol communication
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.
AI and inclusion, Alternative and augmentative communication, Complex communication needs, Web accessibility
59-66
Wald, Michael
90577cfd-35ae-4e4a-9422-5acffecd89d5
Draffan, E.A.
021d4f4e-d269-4379-ba5a-7e2ffb73d2bf
Ding, Chaohai
f92dff41-8249-46b3-9a73-284a3bd286ac
Wald, Michael
90577cfd-35ae-4e4a-9422-5acffecd89d5
Draffan, E.A.
021d4f4e-d269-4379-ba5a-7e2ffb73d2bf
Ding, Chaohai
f92dff41-8249-46b3-9a73-284a3bd286ac

Wald, Michael, Draffan, E.A. and Ding, Chaohai (2020) AI and global AAC symbol communication. Lecture Notes in Computer Science, 12376, 59-66. (doi:10.1007/978-3-030-58796-3_8).

Record type: Article

Abstract

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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AI_and_Global_AAC_Symbol_Communication_finalEA2 - Author's Original
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More information

Published date: 4 September 2020
Keywords: AI and inclusion, Alternative and augmentative communication, Complex communication needs, Web accessibility

Identifiers

Local EPrints ID: 445080
URI: http://eprints.soton.ac.uk/id/eprint/445080
PURE UUID: 42e332fc-e7cf-4779-afdb-6f9c71807324

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Date deposited: 19 Nov 2020 17:30
Last modified: 19 Nov 2020 17:30

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Contributors

Author: Michael Wald
Author: E.A. Draffan
Author: Chaohai Ding

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