Title
Automatic word alignment tools to scale production of manually aligned parallel texts.
Abstract
We have been creating large-scale manual word alignment corpora for Arabic-English and Chinese-English language pairs in genres such as newsire, broadcast news and conversation, and web blogs. We are now meeting the challenge of word aligning further varieties of web data for Chinese and Arabic "dialects". Human word alignment annotation can be costly and arduous. Alignment guidelines may be imprecise or underspecified in cases where parallel sentences are hard to compare - due to non-literal translations or differences between language structures. In order to speed annotation, we examine the effect that seeding manual alignments with automatic aligner output has on annotation speed and accuracy. We use automatic alignment methods that produce alignment results which are high precision and low recall to minimize annotator corrections. Results suggest that annotation time can be reduced by up to 20%, but we also found that reviewing and correcting automatic alignments requires more time than anticipated. We discuss throughout the paper crucial decisions on data structures for word alignment that likely have a significant impact on our results.
Year
Venue
Keywords
2012
LREC 2012 - EIGHTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
word alignment,machine translation,annotation bootstrapping
Field
DocType
Citations 
Broadcasting,Data structure,Annotation,Conversation,Arabic,Computer science,Speech recognition,Artificial intelligence,Natural language processing,Recall
Conference
2
PageRank 
References 
Authors
0.42
8
3
Name
Order
Citations
PageRank
Stephen Grimes1274.56
Katherine Peterson2192.24
Xuansong Li3729.93