Learn More
Vocal fold (VF) motion is a fundamental process in voice production, and is also a challenging problem for direct numerical computation because the VF dynamics depend on nonlinear coupling of air flow with the response of elastic channels (VF), which undergo opening and closing, and induce internal flow separation. A traditional modeling approach makes use(More)
A two space dimensional active nonlinear nonlocal cochlear model is formulated in the time domain to capture nonlinear hearing effects such as compression, multi-tone suppression and difference tones. The micromechanics of the basilar membrane (BM) are incorporated to model active cochlear properties. An active gain parameter is constructed in the form of a(More)
Voiced-unvoiced-silence classhation of speech was made using a multilayer feedforward network. The network was evaluated and compared to a maximum-likelihood classiller. Results indicated that the network performance was not significantly affected by the size of training set and a classification rate as high as 96% was obtained.
We took a multi-resolution approach to the signature verification problem. The top-level representation of signatures was the global geometric features. A multi-resolution representation of signatures was obtained using the wavelet transformation. We built VQ and network classifiers to demonstrate the advantages of the multi-resolution approach. High(More)
The blind source separation problem arises when one attempts to recover source signals from their linear mixtures without detailed knowledge of the mixing process. Solutions are nonunique and have degrees of freedom in scaling and permutation. One may impose equality (hard) constraints to fix these scaling parameters; however, small divisor problems may(More)
We study an efficient dynamic blind source separation algorithm of convolutive sound mixtures based on updating statistical information in the frequency domain, and minimizing the support of time domain demixing filters by a weighted least square method. The permutation and scaling indeterminacies of separation, and concatenations of signals in adjacent(More)
A time domain blind source separation algorithm of convolutive sound mixtures is studied based on a compact partial inversion formula in closed form. An l 1-constrained minimization problem is formulated to find demixing filter coefficients for source separation while capturing scaling invariance and sparseness of solutions. The minimization aims to reduce(More)
A perception and PDE (partial diierential equation) based nonlinear transformation is proposed to process spoken words in noisy environment. The transformation was designed to reduce noise through time adaptation and spectral enhancement b y e v olving a focusing quadratic fourth order nonlinear PDE (the Cahn-Hillard equation). Constant, low SNR signals(More)