Abstract
This paper describes a language independent method for alignment of parallel texts that re-uses acquired knowledge. The system extracts word translation equivalents and re-uses them as correspondence points in order to enhance the alignment of parallel texts. Points that may cause misalignment are filtered using confidence bands of linear regression analysis instead of heuristics, which are not theoretically reliable. Homographs bootstrap the alignment process so as to build the primary word translation lexicon. At each step, the previously acquired lexicon is re-used so as to repeatedly make finer-grained alignments and produce more reliable translation lexicons.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
