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CWI Amsterdam The Netherlands Supporting the Generation of Argument Structure within Video Sequences
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Talk Outline The motivation and vision of the work What is needed Annotations Editing Process Editor Support Conclusions
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Existing Documentaries Traditional video authoring: the footage is selected and edited for the final cut there is only one final version, what is shown is the choice of the author / editor Material can be very rich and controversial (e.g. Voices of Iraq)
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New Paradigm Proposed video authoring: Annotate the video material semantics Edit it automatically, selecting what the user asks to see Use the Web as an interactive distribution mean More than a sequence of matching video fragments): Argumentation/rhetoric Narrative
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Video material Interview with America: video footage with interviews and background material about the opinion of American people after 9-11 www.interviewwithamerica.com Annotations: 1 hour annotated, 15 interviews, 60 interview segments, 120 statements
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What do you think of the war in Afghanistan?
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Example Explained Claim Concession Claim contradict support Claim I am not a fan of military actions War has never solved anything Two billions dollar bombs on tents I cannot think of a more effective solution weaken
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The annotations Rhetorical Argumentation model: Toulmin model Rhetorical Statement (mostly verbal, but visual also possible) Descriptive Question asked Interviewee (social) Filmic (e.g. location/time/framing/gaze)
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Encode statements Statement formally annotated: E.g. “war best solution” A thesaurus containing: Terms for each part (155 in total) Relations between terms: similar (72), opposite (108), generalization (10), specialization (10) E.g. war opposite diplomacy Relations in the thesaurus determine link type between statements
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Automatic Linking Process STEP1: Using the thesaurus, generate related statements, by replacing iteratively terms: E.g. from “war best solution” “diplomacy best solution”, “war not solution” STEP2: Query the repository to see whether the statement is present
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Connect statements Create a graph of related statements Nodes are the statements (video segments), edges are either support or contradict S1 S2 S3 S5 S4 S7 S6 S8 S9 S0 = support = contradict
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Author/Annotator support Capability of generating different arguments depends on the quality of the Semantic Graph Statements (and corresponding video segments) not connect are lost for generation: Our case: out of 118 statements 54 were not connected Measure the performance of the automatic linking process
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Indices for statements Measure how many statements are generated from a given one: depends on the quantity of the relations in the thesaurus Measure how many generates statements are present in the repository Depends on correctness of the relations in the thesaurus
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Index for relations Measure how a particular relation in the thesaurus is performing: If a generated statement is present in the repository, the relations used to generate it get one point on a hit score, otherwise one point on the miss score The ratio hit/miss gives an idea of the semantic accuracy of the relation with respect to the repository
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Current/future Work Automatic Relation suggestion: Start with a fully connected thesaurus, keep only best relations Suggest best relation to add to existing ones Linking Process tuning Currently 3 iterations for performance, but the process runs of-line: more iterations possible Different repositories (VJ project)
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Conclusions New documentary production mechanism, multiple versions Different authoring, author does not have full control anymore Authoring support needed
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Questions? Thanks for your attention
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Pointers & Acknowledgments This presentation and Demo available at: http://www.cwi.nl/~media/demo/IWA/ This research was funded by the Dutch national ToKeN2000 I 2 RP and CHIME projects.
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Author/Annotator support Provide means to measure the performance of the creation of the Semantic Graph Reengineer the Semantic Graph generation: Changing annotations Changing relations in the Thesaurus
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What do you think of the war in Afghanistan? I am not a fan of military actions War has never solved anything I cannot think of a more effective solution Two billions dollar bombs on tents
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Toulmin model ClaimData Qualifier WarrantBackingConditionConcession 57 Claims, 16 Data, 4 Concessions, 3 Warrants, 1 Condition
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