Expanding small corpora to aid people with communication impairment

Difficulties in the communication of people with various movement and cognitive disorders may be alleviated by means of pictorial symbols. Automatic transformation of symbol sequences to natural language is of high importance. Performing this task by defining all valid sentences manually would require a large amount of work. We show that a small initial seed corpus is sufficient, which can be expanded automatically by generating candidate sentences and filtering them using A-gram statistics from a much larger corpus. The method is evaluated on a seed corpus containing dialogues, collected from an English language learning website. The ratio of useful sentences in the expanded corpus is 3-4 times bigger than in the set of unfiltered candidate sentences. We also use a manually constructed corpus for further evaluation. To demonstrate the practical applicability of the method, we have implemented a sentence production prototype that performs the transcription of symbol sequences to natural language. The system produces new and meaningful sentences and thus it can considerably decrease the size of the corpus needed, while it can increase the variability of sentences

What is the potential for context aware communication aids?

Use of voice output communication aids (VOCAs) can be a very effective strategy to assist people with speech impairments in communicating. Despite this, people who use communication aids often express frustration with VOCAs—desiring devices that are simpler, quicker and more effective to use. Whilst it is not possible to resolve all these issues with technology, it is argued that significant progress can be made. The use of contextual information is one development that could improve the simplicity and effectiveness of communication aid design. Improving the effectiveness of communication aids, including through the use of context support, is a goal of the NIHR Devices for Dignity Assistive Technology Theme. This discussion paper examines the potential for creating ‘context aware’ communication aids. Three projects in which the authors have been involved are described to illustrate different approaches to the use of contextual information

ARTIFICIAL INTELLIGENCE IN AUGMENTATIVE AND ALTERNATIVE COMMUNICATION SYSTEMS - A LITERATURE-BASED ASSESSMENT AND IMPLICATIONS OF DIFFERENT CONVERSATION PHASES AND CONTEXTS

Even though AAC systems and corresponding AI approaches have been investigated in the extant research, they still show remarkable drawbacks, resulting in a low prevalence among speech-impaired individuals. As the suggestions and adaptions proposed by AI within AAC systems may show insufficiencies in certain situations (e.g., unreliable suggestions, low conversational rates, unauthentic adaptions towards the users), we aim to take a more up-close look at the conversations, especially the conversational contexts and conversation phases in which the supporting AI is applied. Therefore, we have conducted a Systematic Literature Review as well as Literature Analysis. Thereby, we could reveal that there are indeed several gaps within the extant research on AI regarding the coverage of the conversational context “informativeness” and the conversation phases “beginning” and “closing”. To dismantle the existing communication barriers that speech-impaired individuals suffer from, several implications for investigating AI in the context of AAC systems are derived and proposed for future (IS) research

A concept-environment for computer-based augmentative and alternative communication founded on a systematic review

Introduction: locked-In Syndrome is admittedly the worst case of motor and speech impairment, it seriously damages the ability of oral and gestural communication of patients. In recent years, alternative and augmentative communication technology has provided resources to restore these patients' ability to communicate. Methods: in order to relate and classify the main methods with that purpose, this work conducted a systematic review on several journal databases. Results: we found 203 related papers and 55 of them were selected to compose the study. After that, we classified them into three major groups and we identified the main difficulties when using each approach. Conclusion: in order to overcome these difficulties, we propose a new system concept to develop an adaptive, robust and low cost communication environment. The proposed system is composed of five modules: data entry, communication, aid to the caregiver and external interaction

ARTIFICIAL INTELLIGENCE IN AUGMENTATIVE AND ALTERNATIVE COMMUNICATION SYSTEMS – A LITERATURE-BASED ASSESSMENT AND IMPLICATIONS OF DIFFERENT CONVERSATION PHASES AND CONTEXTS

Even though AAC systems and corresponding AI approaches have been investigated within the extant research, they still show remarkable drawbacks, resulting in a low prevalence among speech-impaired individuals. As the suggestions and adaptions proposed by AI within AAC systems may show insufficiencies in certain situations (e.g., unreliable suggestions, low conversational rates, unauthentic adaptions towards users), we take an up-close look, especially at the conversation phases and contexts in which the supporting AI is applied. Therefore, we have conducted a systematic literature review as well as a literature analysis. Thereby, we could reveal that there are indeed several gaps within the extant research on AI regarding the coverage of the conversational context “informativeness” and the conversation phases “beginning” and “closing”. To dismantle the existing communication barriers that speech-impaired individuals suffer from, several implications for investigating AI in the context of AAC systems are derived and proposed for future (IS) research

Towards the improvement of Augmentative and Alternative Communication through the modelling of conversation. Towards the improvement of Augmentative and Alternative Communication through the modelling of conversation Towards the improvement of AAC through

Abstract: Non-speaking people who use Augmentative and Alternative Communication (AAC) systems typically have low rates of communication which reduces their ability to interact with others. Research and development continues in the quest to improve the effectiveness of AAC systems in terms of communication rate and impact. One strategy involves making the basic unit of communication an entire utterance, and designing the AAC system to make the storage, retrieval and production of utterances as easy and efficient as possible. Some approaches take this further and include texts, narratives and/or multimedia material for use in conversation. AAC systems operating in such a manner require a structure for containing and managing conversational material and supporting the production of output during conversation. Ideally such a structure should be modelled on the way actual conversations proceed. A number of partial models for this have been presented thus far. These are reviewed in the paper and an integrated model is then proposed that includes both the structure of a conversation and the way in which an AAC system might produce conversational output (e.g. utterances, texts, multimedia items or combinations of these). Modelling the process in this way gives a structure with which an AAC system can organize the support and guidance that it offers to the person using the system. The paper concludes with consideration of three areas of development for further investigation