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.
We examine the problem of how the Hopfield net associative memory framework can be adapted for speech recognition, by first identifying specific issues in such an adaptation, such as i) the problem of representing spectral feature vector sequences in the form of time normalized time-frequency (t-f) constellations, ii) the issue of limited capacity of the network when the temporal patterns are highly...
We address the problem of audio analytics with respect to efficient modeling of audio classes and continuous decoding of audio stream to automatically segment and label the audio stream as required in audio indexing. We propose the use of left-to-right HMMs and ergodic HMMs to respectively model definite and indefinite duration audio classes and Viterbi decoding using these HMMs with non-emitting...
We propose an online session-adaptation algorithm for making variable-text speaker-recognition systems robust to inter-session variability, by a continuous update of registered speakers' multiple templates from test utterances during actual usage of the system. The algorithm is set in a speaker-verification mode of operation and uses an enhanced verification step to ensure reliable selection of input...
The problem of the effect of accent on the performance of Automatic Speech Recognition (ASR) systems is well known. In this paper, we study the effect of accent variability on the performance of the Indian English ASR task. We evaluate the test vocabularies on HMMs trained on (a) Accent specific training data (b) Accent pooled training data which combines all the accent specific training data (c)...
In this paper, we propose a fast method to recognize human actions which accounts for intra-class variability in the way an action is performed. We propose the use of a low dimensional feature vector which consists of (a) the projections of the width profile of the actor on to an ldquoaction basisrdquo and (b) simple spatio-temporal features. The action basis is built using eigenanalysis of walking...
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.