These may be words in word-based alignment models or single characters in character-based alignment models.1 We define our alignment as of, where each element is a span ak = (s, t, u, 2)) indicating that the target string es, .

The most well-known and widely-used models for bitext alignment are for one-to-many alignment, including the IBM models (Brown et al., 1993) and HMM alignment model (Vogel et al., 1996).

One barrier to applying many-to-many alignment models to character strings is training cost.

Secondly, we describe a method to seed the search process using counts of all substring pairs in the corpus to bias the phrase alignment model .

Sparsity causes trouble for alignment models , both in the form of incorrectly aligned uncommon words, and in the form of garbage collection, where uncommon words in one language are incorrectly aligned to large segments of the sentence in the other language (Och and Ney, 2003).