By I. Dan Melamed
Parallel texts (bitexts) are a goldmine of linguistic wisdom, as the translation of a textual content into one other language could be seen as a close annotation of what that textual content ability. wisdom approximately translational equivalence, which might be gleaned from bitexts, is of crucial significance for functions comparable to guide and computing device translation, cross-language info retrieval, and corpus linguistics. the supply of bitexts has elevated dramatically because the creation of the net, making their examine an exhilarating new zone of analysis in common language processing. This publication lays out the speculation and the sensible strategies for locating and using translational equivalence on the lexical point. it's a start-to-finish consultant to designing and comparing many translingual applications.
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Extra resources for Empirical Methods for Exploiting Parallel Texts
The algorithm sorts all chains on how many other chains they conflict with and eliminates them in this sort order, one at a time, until no conflicts remain. Whenever two or more chains are tied in the sort order, the conflict resolution algorithm eliminates all but the chain with the least point dispersal. Additional Search Passes To ensure that SIMR rejects spurious chains, the maximum angle deviation threshold must be set low. However, like any heuristic filter, this one will reject some perfectly valid candidates.
SIMR exploits these properties to decide which chains might be TPC chains. First, chains that lack the injectivity property are rejected outright. The remaining chains are filtered using two threshold parameters: maximum point dispersal and maximum angle deviation. The linearity of each chain is measured as the root mean squared distance of the chain’s points from the chain’s leastsquares line. If this distance exceeds the maximum point dispersal threshold, the chain is rejected. The angle of each chain’s least-squares line is compared to the arctangent of the bitext slope.
The distance between a bitext map and each TPC can be defined in a number of ways. 9 Two text segments at the end of Sentence A were switched during translation, resulting in a non-monotonic segment. To interpolate injective bitext maps, non-monotonic segments must be encapsulated in Minimum Enclosing Rectangles (MERs). A unique bitext map can then be interpolated by using the lower left and upper right corners of the MER (map M2), instead of the non-monotonic correspondence points (function M1).