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In this paper a feature extraction technique using Reconstructed Phase Spaces (RPS) is presented, which improves the overall performances of typical speech recognition systems. Unlike conventional feature extraction methods that use FFT based algorithm as power spectrum estimation (PSE) of speech signal, the proposed method is based on the trajectory and flow matrix of signal's RPS. In this manner,...
As e-commerce sales continue to grow, the associated online fraud remains an attractive source of revenue for fraudsters. These fraudulent activities impose a considerable financial loss to merchants, making online fraud detection a necessity. The problem of fraud detection is concerned with not only capturing the fraudulent activities, but also capturing them as quickly as possible. This timeliness...
Eigenspace-based speaker adaptation approaches, such as eigenvoice (EV) and eigenspace-based MLLR (EMLLR) have been shown to be more effective than traditional speaker adaptation algorithms for rapid adaptation tasks. In these methods, principal component analysis (PCA) is applied to a diverse set of speaker characteristics to extract orthogonal basis vectors which include the most variations of speakers'...
Content based image retrieval, the problem of finding images from data base according to their content, has been the subject of a significant amount of research in the last decade. Image retrieval based on region is one of the most promising and active research directions in recent years. As literature prove that region segmentation will produce better results. Human visual perception is more effective...
We present a new method to learn the model based on object parts extraction and grammar which can be applied to classification and recognition. Our approach is invariant to the scale and rotation of the objects. We use Structural Context feature to detect object parts. It is done comparing SC histograms of the model and image. We extract oriented triplets from centers of detected parts. We define...
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