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.
Keyword spotting (KWS) is an essential technique for speech information retrieval. When doing offline keyword query on large volume spontaneous speech data, fast and accurate KWS methods are required. In this paper, a novel phone-state matrix based vocabulary-independent KWS method is proposed, which has merits of both hidden Markov model (HMM) based and lattice-based methods. Four KWS systems are...
In this paper, we first review two approaches in the context of robust recognition, e.g. speech enhancement based two-stage mel-warp Wiener filtering (MWF) (A. Agarwal and Y.M. Cheng, 1999) and first-order vector Taylor series (VTS) (P.J. Moreno et al., 1996) compensation in log power spectrum, which are widely used. A new noise robust front-end is proposed, in which VTS compensation derived statistics...
The task of keyword spotting is to detect a set of keywords in the input continuous speech. The main goal of this work is to develop an improved Mandarin keyword spotting (KWS) system for conversational telephone speech (CTS). In this paper, we propose an efficient online-garbage model based KWS system, which integrated with a word-level minimum classification error (MCE) training method and a novel...
Support Vector Machines have merged as a pattern classifier and have been shown to be successful in some tasks in the realm of speech processing. This paper explores the issues involved in applying SVMs to asymmetrical situations, namely. beavy sample ratio bias between different classes and different costs for different types of misclassification error. We also present our revisions on the SMO algorithm...
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.