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.
This paper examines multilingual audio Query-by-Example (QbE) retrieval, utilizing the posteriorgram-based Phonetic Unit Modelling (PUM) approach and the Weighted Fast Sequential Dynamic Time Warping (WFSDTW) algorithm. The PUM approach employs phone recognizers trained on language-specific external resources in a supervised way. Thus, the information about the phonetic distribution is embedded in...
We introduce a novel approach to Query-by-Example (QbE) retrieval, utilizing fundamental principles of posteriorgram-based Spoken Term Detection (STD), in this paper. Proposed approach is a kind of modification of widely used seg-mental variant of dynamic programming algorithm. Our solution represents sequential variant of DTW algorithm, employing one step forward moving strategy. Each DTW search...
The evaluation of two classification architectures utilizing the rule-based approach and the one-against-one support vector machine (OAO-SVM) is presented in this paper. The classification of the audio stream is carried out in two steps. At first, the rule-based speech/non-speech and music/environment sound discrimination is conducted. The set of adopted features, with a high efficiency in separation...
Audio classification is one of the most important task in content-based analysis and can be implemented in many audio applications, such as indexing and retrieving. This paper addresses the problem of broadcast news audio classification, by support vector machine - binary tree (SVM-BT) architecture, into the five classes: pure speech, speech with music, speech with environment sound, pure music and...
The paper presents the support vector machine binary decision tree scheme (SVM-BDT) used for broadcast news (BN) audio classification. The SVM-BDT architecture was designed to solve multi-class discrimination problem of considered acoustic events: pure speech, speech with music, speech with environment sound, music, and environment sound. Its performance was investigated by using Mel-frequency cepstral...
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.