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Interactive information visualization is an emerging and powerful research technique that can be used to understand models of language and their abstract representations. Much of what computational linguists fall back upon to improve NLP applications and to model language “understanding” is structure that has, at best, only an indirect attestation in observable data. An important part of our research progress thus depends on our ability to fully investigate, explain, and explore these structures, both empirically and relative to accepted linguistic theory. . | Interactive Visualization for Computational Linguistics Christopher Collins and Gerald Penn Department of Computer Science University of Toronto 10 King s College Road Toronto Ontario Canada ccollins gpenn @cs.utoronto.ca Sheelagh Carpendale Department of Computer Science University of Calgary 2500 University Dr. NW Calgary Canada sheelagh@ucalgary.ca Interactive information visualization is an emerging and powerful research technique that can be used to understand models of language and their abstract representations. Much of what computational linguists fall back upon to improve NLP applications and to model language understanding is structure that has at best only an indirect attestation in observable data. An important part of our research progress thus depends on our ability to fully investigate explain and explore these structures both empirically and relative to accepted linguistic theory. The sheer complexity of these abstract structures and the observable patterns on which they are based usually limits their accessibility often even to the researchers creating or attempting to learn them. To aid in this understanding visual externaliza-tions are used for presentation and explanation traditional statistical graphs and custom-designed illustrations fill the pages of ACL papers. These visualizations provide post hoc insight into the representations and algorithms designed by researchers but visualization can also assist in the process of research itself. There are special statistical methods falling under the rubric of exploratory data analysis and visualization techniques just for this purpose in fact but these are not widely used or even known in CL. These techniques offer the potential for revealing structure and detail in data before anyone else has noticed them. When observing natural language engineers at work we also notice that even without a formal visualization background they often create sketches to aid in their understanding and communication of
