The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Language model adaptation using text data downloaded from the WWW is an efficient way to train a topic-specific LM. We are developing an unsupervised LM adaptation method using data in the Web. The one key point of unsupervised Web-based LM adaptation is how to select keywords to compose the search query. In this
Query-recommendation systems based on inputted queries have become widespread. These services are effective if users cannot input relevant queries. However, the conventional systems do not take into consideration the relevance between recommended queries. This paper proposes a method of obtaining related queries and clustering them by using the history of query frequencies in query logs. We define...
is no matched word (common word) in both sentences. In addition; if an itinerary is recorded as "Go to TENCON conference on next Monday" such a speech sentence will face difficulties for the future SDR. The timing keywords "next Monday" which is not a datable schedule leads to a query input: "Any trip on November 24
results in up to 1.1% absolute Word Error Rate (WER) improvement as compared to keyword-based approaches. The proposed approach reduces the WER by 6.3% absolute in our experiments, compared to an in-domain LM without considering any Web data.
Rooted in multi-document summarization, maximum marginal relevance (MMR) is a widely used algorithm for meeting summarization (MS). A major problem in extractive MS using MMR is finding a proper query: the centroid based query which is commonly used in the absence of a manually specified query, can not significantly outperform a simple baseline system. We introduce a simple yet robust algorithm to...
This paper described our development dialog system on Kyoto tourist information assistance. Dialog part of our system helped user to make an appropriate query. Information analysis part would be assisted for user to select the retrieved information. Nowadays we can get most information through the Internet. However, we have a trouble to pick up expected information from the huge results with conventional...
General purpose search engines provide users with lists of retrieved documents in response to their queries. The common structure of list elements includes the title of a document, its URL, and small snippet from the text. Snippets are evidence of occurrences of query's keywords in the document. The length of each
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.