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.
A key challenge in rapidly building Tibetan language speech recognition applications is minimizing the manual effort required in transcribing and labeling speech data. Accurate labeling of Tibetan speech utterances is extremely time consuming and requires trained linguists. For alleviate this problem, we present an approach that aims at reducing the amount of manually transcribed speech data required...
Adaptive boosting (AdaBoost) learning method can improve the performance of a base classifier by mining feature information in depth. But it is computationally expensive, and the base classifier without a suitable accuracy will cause over fitting. In this paper an improved Adaboost algorithm using maximum a posteriori vector quantization model (VQMAP) for speaker identification is presented. A suitable...
Aiming at the problem of Tibetan speech recognition under the condition of resistance from noise, a kind of Tibetan speech recognition algorithm, combining RBF network with auditory feature was presented in this paper. The description for the Tibetan speech signals was carried out with Mel frequency cepstrum constant (MFCC), and the recognition classifier was designed based on RBF network with the...
MBBNTree algorithm, which integrates the advantage of Markov blanket Bayesian networks (MBBN) and decision tree, would behave better performance than other Bayesian networks for classification. But the available training samples with actual classes are not enough for building MBBNTree classifier in practice. Active learning aims at reducing the number of training examples to be labeled by automatically...
The available cases with actual classes are not enough for building telecom clientspsila credit classification model in practice, especially for the newly established system in which old customerspsila data do not exist. For evaluating telecom clientspsila credit, a classifier based on active learning is proposed in this paper. Active learning aims at reducing the number of training examples to be...
Ear recognition is proved to be a promising authentication technique. Because of earpsilas special physiological structure and location, the fusion of ear and face biometrics could fully utilize their connection relationship of physiological location and the supplement between these two biometrics, and possess the advantage of recognizing people without their cooperation. In this paper a novel feature...
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.