Traditionally, statistical machine translation systems have relied on parallel bi-lingual data to train a translation model. While bi-lingual parallel data are expensive to genera...
Matthew G. Snover, Bonnie J. Dorr, Richard M. Schw...
This study is aimed at investigating whether automatic phonetic transcription procedures can approximate manual transcriptions typically delivered with contemporary large speech c...
Christophe Van Bael, Lou Boves, Henk van den Heuve...
Performance of n-gram language models depends to a large extent on the amount of training text material available for building the models and the degree to which this text matches...
Recent work on the transfer of semantic information across languages has been recently applied to the development of resources annotated with Frame information for different non-En...
Roberto Basili, Diego De Cao, Danilo Croce, Bonave...
Untranslated words still constitute a major problem for Statistical Machine Translation (SMT), and current SMT systems are limited by the quantity of parallel training texts. Augm...