The Mathematics of Statistical MT (IBM alignment models)

Editorial record

Plain-language summary

The paper frames translation as finding the target sentence most probable given the source, decomposed via Bayes' rule into a translation model and a language model, and introduces a hidden alignment variable saying which source word generated each target word. The five IBM models add successive detail (word translation probabilities, then absolute position, fertility of how many words a source word produces, and distortion of position), and their parameters are estimated from unaligned sentence pairs using the EM algorithm. These alignment models became the statistical foundation of machine translation for roughly two decades and the basis for later phrase-based systems.