UIMAbased MEMT: MultiEngine Machine Translation

1
UIMA-based MEMTMulti-Engine Machine Translation

• Faculty
• Alon Lavie, Jaime Carbonell, Eric Nyberg
• Students and Staff
• Gregory Hanneman, Justin Merrill
• (Shyamsundar Jayaraman, Satanjeev Banerjee)

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MEMT Goals and Approach

• Combine the output of multiple MT engines into a
  synthetic output that outperforms the originals
  in translation quality
• Synthetic combination of the originals, NOT
  selecting the best system

3
Synthetic Translation MEMT

• Approach
• Start with output sentences of the various MT
  engines
• Explicitly align the words that are common
  between any pair of systems, and apply
  transitivity
• Use the alignments as reinforcement and as
  indicators of possible locations for the words
• Each engine has a weight that is used for the
  words that it contributes
• Decoder searches for an optimal synthetic
  combination of words and phrases that optimizes a
  scoring function that combines the alignment
  weights and a LM score

4
Architecture and Engineering

• Challenge How do we construct an effective
  architecture for running MEMT within large-scale
  distributed projects?
• Example GALE Project
• Multiple MT engines running at different
  locations
• Input may be text or output of speech
  recognizers, Output may go downstream to other
  applications (IE, Summarization, TDT, etc.)
• Approach Using IBMs UIMA Unstructured
  Information Management Architecture
• Provides support for building robust processing
  workflows with heterogeneous components
• Components can act as annotators at the
  character level within documents

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UIMA-based MEMT

• MT engines and MEMT engine are set up as
  distributed servers
• Communication over socket connections
• Sentence-by-sentence translation
• Java wrappers convert these into UIMA-style
  annotator components
• UIMA-based workflows implement a variety of
  independent tasks, with results stored in a
  common Annotations Database (ADB)
• Translation workflows
• MEMT workflow
• Evaluation/scoring workflow

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UIMA-based MEMT Examples

• Translation Workflow
• Retrieve document from ADB
• Annotate document with translation annotator X
• Write back new annotation into ADB

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UIMA-based MEMT Examples

• MEMT Workflow
• Retrieve document translation annotations labeled
  by X, Y, Z from ADB
• Annotate the document with a new MEMT
  annotation
• Write back MEMT annotation into ADB

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Conclusions and Open Research Issues

• New sentence-level MEMT approach with promising
  performance (details?)
• Easy to run on both research and COTS systems
• UIMA-based architecture design for effective
  integration is large distributed systems/projects
  ? GALE
• Main Open Research Issues
• Improvements to the underlying algorithm better
  word alignments, artificial word alignments
• Confidence scores at the sentence or word level
• Decoding is still suboptimal
• Oracle scores show there is much room for
  improvement
• Need for additional discriminant features
• Extend approach to Multi-Engine SR combination
• Engineering issues synchronization, human
  friendly interfaces with workflows