We present a new technique for achieving source separation when given only a single charmel recording. The main idea is based on exploiting the inherent time structure of sound sources by learning a priori sets of time-domain basis functions that encode the sources in a statistically efficient manner. We derive a learning algorithm using a maximum likelihood approach given the observed single charmel data and sets of basis functions. For each time point we infer the source parameters and their contribution factors. This inference is possible due to the prior knowledge of the basis functions and the associated coefficient densities. A flexible model for density estimation allows accurate modeling of the observation, and our experimental results exhibit a high level of separation performance for simulated mixtures as well as real environment recordings employing mixtures of two different sources. We show separation results of two music signals as well as the separation of two voice signals.

We apply independent component analysis (ICA) for extracting an optimal basis to the problem of finding efficient features for representing speech signals of a given speaker The speech segments are assumed to be generated by a linear combination of the basis functions, thus the distribution of speech segments of a speaker is modeled by adapting the basis functions so that each source component is statistically independent. The learned basis functions are oriented and localized in both space and frequency, bearing a resemblance to Gabor wavelets. These features are speaker dependent characteristics and to assess their efficiency we performed speaker identification experiments and compared our results with the conventional Fourier-basis. Our results show that the proposed method is more efficient than the conventional Fourier-based features in that they can obtain a higher speaker identification rate.

This paper proposes a hybrid method for vibration analysis in the medium to high frequency ranges using Power Flow Analysis (PFA) algorithm and Statistical Energy Analysis (SEA) coupling concepts. The main part of the developed method is the application of coupling loss factor (CLF) suggested in SEA to the power transmission, reflection coefficients in PI' A boundary conditions. The developed hybrid method shows very promising results with regard to the applications for the various damping loss factors in wide frequency ranges. And also this paper presents the applied results of Power Flow Finite Element Method (PFFEM) by forming the new joint element matrix with CLF to analyze the various plate structures in shape. The analytical results of automobile, complex plate structures show good agreement with those of PFFEM using the PFA coefficients.

The goal of the present research is to improve a quality of life of the elderly with a dementia. In this paper, it is realized by developing the dialog system that is controlled by three kinds of modules such as speech recognition engine, graphical agent, or database classified by a nursing schedule. The system was evaluated in an actual environment of a nursing facility by introducing it to an older male patient with dementia. The comparison study between dialog system and professional caregivers was then carried out at nursing home for 5 days in each case. The evaluation results showed that the dialog system was more responsive in catering to needs of dementia patient than professional caregivers. Moreover, the proposed system led the patient to talk more than caregivers did.

In this paper, we propose an adaptive wavelet method for car interior noise cancellation. For this purpose, we use a node dependent threshold which minimizes the Bayesian risk. We propose a noise estimation method based on spectral entropy using histogram of intensity and a candidate best basis instead of Donoho's best bases. And we modify the hard threshold function. Experimental results show that the proposed algorithm is more efficient, especially to heavy noisy signal than conventional one.

In this paper, the strong in-plane vibration has been experimentally observed at the end of a finite cylindrical shell. The strong in-plane vibration was generated by the evanescent wave field, which was excited along about half the length of the shell. The evanescent waves were generated due to mode conversion of elastic waves at the ends of the cylindrical shells. The results show that the strong in-plane end vibration can be generated in cylindrical shells.