Alternative and Augmentative Communication (AAC) for people with speech and language disorders is an interesting and challenging application field for research in Natural Language Processing. Further advances in the development of AAC systems require robust language processing techniques and versatile linguistic knowledge bases. Also NLP research can benefit from studying the techniques used in this field and from the user-centred methodologies used to develop and evaluate AAC systems. Until recently, however, apart from some exceptions, there was little scientific exchange between the two research areas. This paper aims to make a contribution to closing this gap. We will argue that current interest in language use, which can be shown by the large amount of research on comprehensive dictionaries and on corpora processing, makes the results of NLP research more relevant to AAC. We will also show that the increasing interest of AAC researchers in NLP is having positive results. To situate research on communication aids, the first half of this paper gives an overview of the AAC research field. The second half is dedicated to an overview of research prototype systems and commercially available communication aids that specifically involve more advanced language processing techniques.

This article focuses on the need for technological aid for agrammatics, and presents a system designed to meet this need. The field of Augmentative and Alternative Communication (AAC) explores ways to allow people with speech or language disabilities to communicate. The use of computers and natural language processing techniques offers a range of new possibilities in this direction. Yet AAC addresses speech deficits mainly, not linguistic disabilities. A model of aided AAC interfaces with a place for natural language processing is presented. The PVI system, described in this contribution, makes use of such advanced techniques. It has been developed at Thomson-CSF for the use of children with cerebral palsy. It presents a customizable interface helping the disabled to compose sequences of icons displayed on a computer screen. A semantic parser, using lexical semantics information, is used to determine the best case assignments for predicative icons in the sequence. It maximizes a global value, the ‘semantic harmony’ of the sequence. The resulting conceptual graph is fed to a natural language generation module which uses Tree Adjoining Grammars (TAG) to generate French sentences. Evaluation by users demonstrates the system's strengths and limitations, and shows the ways for future developments.

In this paper, we present results of a project that investigated the application of lexicon based text retrieval techniques to Alternative and Augmentative Communication (AAC). As a practical outcome of this research, a communication aid based on message retrieval by key words was designed, implemented and evaluated. The message retrieval module in the system uses a large semantic lexicon, derived from the WordNet database, for query expansion. Trials have been carried out with the device to evaluate whether the approach is suitable for AAC, and to determine the semantic relations that lead to efficient message retrieval. The first part of this paper describes the background of the project and highlights the retrieval requirements for a communication aid, which differ considerably from the requirements in standard text retrieval. We then present the overall design of the WordKeys communication aid and describe the tasks of its sub-modules. We summarise trials that have been carried out to determine the effect of semantic query expansion on the success of message retrieval. Evaluation results show that information about word frequency can solve problems that occurred in the semantic query expansion because of taxonomies that have too many intermediate steps between closely related words. Finally, a user evaluation with the improved system showed that full text retrieval is an effective approach to message access in a communication aid.

Non-speaking people often rely on AAC (Augmentative and Alternative Communication) devices to assist them to communicate. These AAC devices are slow to operate, however, and as a result conversations can be very difficult and frequently break down. This is especially the case when the conversation partner is unfamiliar with this method of communication, and is a big obstacle to many people when they wish to conduct simple everyday transactions. A way of improving the performance of AAC devices by using scripts is discussed. A prototype system to test this idea was constructed, and a preliminary experiment performed with promising results. A practical AAC device which incorporates scripts was then developed, and is described.

Augmentative and Alternative Communication (AAC) is the field of study concerned with providing devices and techniques to augment the communicative ability of a person whose disability makes it difficult to speak or otherwise communicate in an understandable fashion. For several years, we have been applying natural language processing techniques to the field of AAC to develop intelligent communication aids that attempt to provide linguistically correct output while increasing communication rate. Previous effort has resulted in a research prototype called Compansion that expands telegraphic input. In this paper we describe that research prototype and introduce the Intelligent Parser Generator (IPG). IPG is intended to be a practical embodiment of the research prototype aimed at a group of users who have cognitive impairments that affect their linguistic ability. We describe both the theoretical underpinnings of Compansion and the practical considerations in developing a usable system for this population of users.