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Using BPM to Analyse the Role of Human Translators in Bitext Management Workflows
Transcript of Using BPM to Analyse the Role of Human Translators in Bitext Management Workflows
Bitext Management Workflow
Dr. David Filip
at CNGL at University of Limerick, Ireland
A structured (usually mark up language based) artefact that contains aligned source (natural language) and target (natural language) sentences. We consider bitex to be ordered by default (such as in an XLIFF file – defined below, an “unclean” rtf file, or a proprietary database representation). Nevertheless, unordered bitext artifacts like translation memories (TMs) or terminology bases (TBs) can be considered special cases of Bitext or bitext aggregates, since the only purpose of TM as an unordered bitext is to enrich ordered bitext, either directly or through training a Machine Translation engine.
Group of processes that consist of high and low level manipulation of ordered and/or unordered bitext artifacts. Agents can be both human and machine. Usually the end purpose of Bitext Management is to create target (natural language) content from source (natural language) content, typically via other enriching Bitext Transforms, so that Bitext Management Processes are usually enclosed within a bracket of source content extraction and target content re-import.
Project Mgmt Point of View
an automated process. This is not a commonplace distinction, but we coin it for practical convenience.
Thanks a million for your attention.. Q&A
Conclusions and Takeaways
L10n organizational setting is complex
Next generation workflows are distributed
Bitext is a hygienic must
(and as such it better be standard rather than proprietary)