  Large bilingual parallel texts (also known as bitexts) are usually stored in
a compressed form, and previous work has shown that they can be more
efficiently compressed if the fact that the two texts are mutual translations
is exploited. For example, a bitext can be seen as a sequence of biwords
---pairs of parallel words with a high probability of co-occurrence--- that can
be used as an intermediate representation in the compression process. However,
the simple biword approach described in the literature can only exploit
one-to-one word alignments and cannot tackle the reordering of words. We
therefore introduce a generalization of biwords which can describe multi-word
expressions and reorderings. We also describe some methods for the binary
compression of generalized biword sequences, and compare their performance when
different schemes are applied to the extraction of the biword sequence. In
addition, we show that this generalization of biwords allows for the
implementation of an efficient algorithm to look on the compressed bitext for
words or text segments in one of the texts and retrieve their counterpart
translations in the other text ---an application usually referred to as
translation spotting--- with only some minor modifications in the compression
algorithm.
