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A new approach is presented for clustering the speakers from unlabeled and unsegmented conversation, when the number of speakers is unknown. In this approach, each speaker is modeled by a Self- Organizing-Map (SOM). For estimation of the number of clusters ...
We propose a new exact Euclidean distance transformation (DT) by propagation, using bucket sorting. A fast but approximate DT is first computed using a coarse neighborhood. A sequence of larger neighborhoods is then used to gradually improve this approxima ...
In recent work, it was proposed to use lossy compression to remove noise from corrupted signals, based on the rationale that a reasonable compression method retains the dominant signal features more than the randomness of the noise. To further understand a ...
In recent years the ``Internet Multicast Backbone'', or MBone, has risen from a small, research curiosity to a large scale and widely used communications infrastructure. A driving force behind this growth was the development of multipoint audio, video, and ...
Some past work has suggested that lossy compression can be a good denoising tool. Building on this theme, we make the connection that quantization of transform coefficients approximates the operation of Donoho-Johnstone's wavelet thresholding, to conclude ...
In recent years, the “Internet Multicast Backbone,” or MBone, has risen from a small, research curiosity to a large- scale and widely used communications infrastructure. A driving force behind this growth was the development of multipoint audio, video, and ...
As recently introduced, an HMM2 can be considered as a particular case of an HMM mixture in which the HMM emission probabilities (usually estimated through Gaussian mixtures or an artificial neural network) are modeled by state-dependent, feature-based HMM ...
As recently introduced, an HMM2 can be considered as a particular case of an HMM mixture in which the HMM emission probabilities (usually estimated through Gaussian mixtures or an artificial neural network) are modeled by state-dependent, feature-based HMM ...
A new set of algorithms for transform adaptation in adaptive transform coding is presented. These algorithms are inspired by standard techniques in adaptive finite impulse response (FIR) Wiener filtering and demonstrate that similar algorithms with simple ...
In this report, we build up on our previous work on speaker clustering, where the number of speakers and segmentation boundaries are unknown a priori. We employ an ergodic HMM with minimum duration topology for this purpose. Starting from a large number of ...
