Abstract
Adjacent symbol connection constraints (ASCCs) are very useful for not only morphological analysis of non-segmenting language such as Japanese language, but also for continuous speech recognition of any language. By incorporating ASCCs into an LR parsing table, it is possible to reduce the size of the table, as well as reject any locally implausible parsing results. Although several algorithms have been proposed, they cannot remove all of the unnecessary actions because they consider only local context. This paper proposes a new algorithm and show some evaluation results. The proposed algorithm incorporates ASCCs by searching for global action chains from the initial state to the final state. According to the results, the proposed algorithm can remove about 1.2% more actions than a conventional algorithm, and the parsing time can be reduced by about 2.4%. Lastly, we show the completeness of our algorithm.
