Combining clues for lexical level aligning using the null hypothesis approach

ABSTRACT

Various informations can be used to align parallel texts at word level: co-occurrence frequencies, position difference, part-of-speech, graphic resemblance, etc. This paper proposes a simple method to combine these clues in an efficient way. The association score is computed from the probabilities of pairing two units under Null hypothesis, assuming that the association is fortuitous. This approach has been applied to a literary English-French parallel text with good results.

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