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In this paper, we report out experiments on NTCIR-11 Spo-kenDoc&Query task for spoken term detection (STD) and spoken content retrieval (SCR). In STD, we consider acoustic feature similarity between utterances over both word and sub-word lattices to deal with the general problem of open vocabulary retrieval with queries of variable length. In SCR, we modify(More)
Headline generation for spoken content is important since spoken content is difficult to be shown on the screen and browsed by the user. It is a special type of abstractive sum-marization, for which the summaries are generated word by word from scratch without using any part of the original content. Many deep learning approaches for headline generation from(More)
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