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	title        = {AAC Language Resources in the Mainstream},
	abstract     = {In order to provide language support to individuals requiring augmentative and alternative communication (AAC) we need linguistic resources suitably organized and represented, e.g., sign language material, symbol and image libraries suitable for multiple cognitive levels, as well as textual support in many languages. So far, these resources have been developed and maintained in separate and uncoordinated efforts, either by commercial or non-profit actors, and targeting different specific groups and needs. In the long run, this is a non-inclusive, ineffective and expensive way of proceeding, leading to limited benefit for AAC users and stake-holders, as well as for potential wider application. In a number of related efforts, work is underway to link free symbol libraries (at present Blissymbols and ARASAAC), where applicable using the Concept Coding Framework (CCF) technology, to common state-of-the-art lexical resources and language technology. The aim is to gradually establish a foundation for inclusive AAC support based on, and included in, mainstream and openly available lexical and language resources for wide use in all sectors of society. Following up results in this area from the European AEGIS project, work is now proceeding in cooperation between DART (centre for AAC and AT), Språkbanken (the Swedish Language Bank) and Centre for language Technology (CLT), University of Gothenburg, Sweden, and others. Results from this work will be presented and demonstrated, and the implications will be discussed. These, and several other signs of the time, strongly indicate that this is way to go.
	booktitle    = {ISAAC-2014 Conference for the International Society for Augmentative and Alternative Communication},
	author       = {Lundälv, Mats and Derbring, Sandra and Ljunglöf, Peter},
	year         = {2014},

	title        = {ShrdLite: Semantic Parsing Using a Handmade Grammar},
	abstract     = {This paper describes my approach for parsing robot commands, which was task 6 at SemEval 2014. My solution is to manually create a compact unification grammar. The grammar is highly ambiguous, and relies heavily on filtering the parse results by checking their consistency with the current world.

The grammar is small, consisting of not more than 25 grammatical and 60 lexical rules. The parser uses simple error correction together with a straightforward iterative deepening search. Nevertheless, with these very basic algorithms, the system still managed to get 86.1% correctness on the evaluation data. Even more interesting is that by making the parser slightly more robust, the accuracy of the system rises to 93.5%, and by adding one single word to the lexicon, the accuracy is boosted to 98.0%.},
	booktitle    = {SemEval-2014 Task 6: Supervised Semantic Parsing of Robotic Spatial Commands},
	author       = {Ljunglöf, Peter},
	year         = {2014},

	title        = {Fast Statistical Parsing with Parallel Multiple Context-Free Grammars},
	abstract     = {We present an algorithm for incremental statistical parsing with Parallel Multiple Context-Free Grammars (PMCFG). This is an extension of the algorithm by Angelov (2009) to which we added statistical ranking. We show that the new algorithm is several times faster than other statistical PMCFG parsing algorithms on real-sized grammars. At the same time the algorithm is more general since it supports non-binarized and non-linear grammars.

We also show that if we make the search heuristics non-admissible, the parsing speed improves even further, at the risk of returning sub-optimal solutions.},
	booktitle    = {EACL'14, 14th Conference of the European Chapter of the Association for Computational Linguistics},
	author       = {Angelov, Krasimir and Ljunglöf, Peter},
	year         = {2014},