Visualizing Data Structures in Parsing-Based Machine Translation
Source: John Hopkins University
As Machine Translation (MT) systems grow more complex and incorporate more linguistic knowledge, it becomes more difficult to evaluate independent pieces of the MT pipeline. Being able to inspect many of the intermediate data structures used during MT decoding allows a more fine-grained evaluation of MT performance, helping to determine which parts of the current process are effective and which are not. This paper presents an overview of the visualization tools that are currently distributed with the Joshua (Li et al., 2009) MT decoder. The paper explains their use and present an example of how visually inspecting the decoder's data structures has led to useful improvements in the MT model.