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Using Confusion Networks for Speech Summarization

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Figure

Figure 1: An example of confusion networks.
Figure 2: Average node density and word coverage of theconfusion networks on the development set.
Table 1: ROUGE results (%) using 1-best hypotheses andhuman transcripts on the development set.
Table 3: ROUGE results (%) on the development setusing different segment representations, with the sum-maries constructed using the corresponding human tran-scripts for the selected segments.
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