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Because unprecedented volumes of multimedia data associated with spoken documents have been made available to the public, spoken document retrieval (SDR) has become an important research area in the past decades. Recently, representation learning has emerged as an active research topic in many machine learning applications owing largely to its excellent performance. In the context of natural language...
Extractive speech summarization, aiming to select an indicative set of sentences from a spoken document so as to concisely represent the most important aspects of the document, has emerged as an attractive area of research and experimentation. A recent school of thought is to employ the language modeling (LM) framework along with the Kullback-Leibler (KL) divergence measure for important sentence...
Query-by-example information retrieval provides users a flexible but efficient way to accurately describe their information needs. The query exemplars are usually long and in the form of either a partial or even a full document. However, they may contain extraneous terms that would have potential negative impacts on the retrieval performance. In order to alleviate those negative impacts, we propose...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.