A Korean Spoken Document Retrieval System for Lecture Search
نویسندگان
چکیده
In this paper, we introduced a Korean spoken document retrieval system for lecture search. We automatically build a general inverted index table from spoken document transcriptions, and we extract additional information from textbooks or slide notes related to the lecture. We integrate these two sources for a search process. The speech corpus used in our system is from a highschool mathematics lecture videos. Experimental results showed that the contents information is slightly beneficial for the lecture spoken document retrieval.
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تاریخ انتشار 2008