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.
There have been proposed spoken dialog systems that utilizes simple database consisted of example sentences and the corresponding reply sentences. However, it is costly to prepare this database manually. In the present study, we propose a framework in which both the example and reply sentences are automatically generated from a database description table that describes minimum information for describing...
In this paper, we proposed a method of retrieving documents from the world wide Web using a spoken document as a ldquokey.rdquo This method can be viewed as a speech version of an ordinary relevant document retrieval, where a text document is used as a query of retrieval. Basically the retrieval is based on an automatic transcription of a spoken document using a speech recognizer. The difficult point...
We developed a system that detects abnormal sound from sound signal observed by a surveillance microphone. Our system learns the ldquonormal soundrdquo from observation of the microphone, and then detects sounds never observed before as ldquoabnormal sounds.rdquo To this end, we developed a technique that uses multiple GMMs for modeling different levels of sound events efficiently. We also consider...
PLSA is one of the most powerful language models for adaptation to a target speech. The vocabulary divided PLSA language model (VD-PLSA) shows higher performance than the conventional PLSA model because it can be adapted to the target topic and the target speaking style individually. However, all of the vocabulary must be manually divided into three categories (topic, speaking style, and general category)...
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 paper, we propose a new method of selecting keywords from keyword candidates, which uses...
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.