Abstract
While most natural language processing systems adopt morphemes as units of processing, humans are known to use larger processing units, which we call cognitive units. The human process of sentence analysis can be considered as consisting of two stages: detection and selection of cognitive units. Based on this idea, this paper proposes a method for sentence analysis which first detects possible cognitive units using a state transition diagram, and then selects correct cognitive units on the basis of their bigrams. The proposed method was applied to text error correction, and the experimental results confirmed that it can achieve a higher performance than that can be attained using morpheme bigrams.
