Abstract
The problem of Error-Correcting Parsing (ECP) using a complete error model and a Finite State Machine (FSM) is examined. This problem arises in many areas of Linguistic and Speech Processing, and is of paramount importance in Syntactical Pattern Recognition, where data is generally distorted or noisy. The Viterbi algorithm can be easily extended to perform ECP using a trellis diagram that has the same number of states as that of the FSM. However, the computational complexity of the ECP process could be prohibitive for real-time pattern recognition tasks. Two different approaches to perform an efficient implementation of such a parsing are suggested. The first one is an adaptation of an extension of the Viterbi algorithm proposed in the literature. In the second one, an algorithm based on a depth-first (“topological”) sort of the states of the FSM, which leads to an efficient processing of the deletion transitions of the underlying error model, is proposed. Experiments are described with results assessing the relative merits of the different techniques.
Work partially supported by the Spanish CICYT under contract TIC93-0633-CO2-01.
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Amengual, J.C., Vidal, E. (1996). Two different approaches for cost-efficient Viterbi parsing with error correction. In: Perner, P., Wang, P., Rosenfeld, A. (eds) Advances in Structural and Syntactical Pattern Recognition. SSPR 1996. Lecture Notes in Computer Science, vol 1121. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61577-6_4
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