Title :
Machine translation in the year 2004
Author :
Knight, Kevin ; Marcu, Daniel
Author_Institution :
Dept. of Comput. Sci., Univ. of Southern California, Marina del Rey, CA, USA
Abstract :
Machine translation (MT) accuracy has recently increased, due to better techniques and to the availability of larger parallel training sets. Statistical MT systems are now able to translate across a wide variety of language pairs. This paper covers the basic elements of state-of-the-art, statistical MT, including modeling, decoding, evaluation, and data preparation.
Keywords :
language translation; statistical analysis; automatic statistical training; data preparation; human language machine translation; language decoding; language modeling; machine translation accuracy; parallel training sets; statistical machine translation; Computer science; Councils; Decoding; Dictionaries; Humans; NIST; Page description languages; Resumes; Security; Viterbi algorithm;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
Print_ISBN :
0-7803-8874-7
DOI :
10.1109/ICASSP.2005.1416466
