We address a problem of speech enhancement: recovering a speech source from a mixture of its delayed versions and additive noise. By using the constrained-optimization technique, the second order statistics based algorithm is developed. The new proposed algorithm requires no strong limitations to the speech signal and the noise. Simulation results show that our algorithm achieves a better performance as compared to other algorithms.

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Speech enhancement using the constrained-optimization technique

The problem of improving the performance of broadband linearly constrained minimum variance (LCMV) adaptive beamforming is considered. A scenario with a single interference source has been investigated. From a numerical analysis, it is found that a suitable choice of the temporal weight spacing which improves the interference rejection performance, depends on the array aperture, as well as the interference direction of arrival. A simple rule for choosing the temporal weight spacing is provided. A method for selecting the weight spacing in practice is suggested. Simulation results for a speech enhancement problem show an improved performance by using the proposed choice of temporal weight spacing.

On optimal temporal weight spacing for broadband LCMV beamforming in the presence of single interference

In this paper, the problem of improving peformance of broadband LCMV adaptive beamforming is considered. Scenario with single interference source has been investigated. From numerical analysis, it is found that suitable choice of temporal weight spacing which improves interference rejection performance, depends on the array aperture, as well as the interference direction of arrival. A simple rule for choosing temporal weight spacing is provided. Method for selecting the weight spacing in practice is suggested. Simulation results for a speech enhancement problem show improved performance by using the proposed choice of temporal weight spacing.

On Optimal Temporal Weight Spacing for Broadband LCMV Beamforming in the Presence of Single Interference

In many voice-related applications, the presence of echoes and overlapping speech signals can degrade the quality or intelligibility of a desired speech signal to be processed It is, therefore, important to cancel the echoes and to separate overlapping speech signals from a mixture of these components, so that a specific function of the system, for instance, transmission, speech identification, or recognition, can be accomplished with better performance However, in many cases we do not know the properties of the communication channel, and sometimes even the number of speech sources is unknown In this paper, we propose to use a reference signal to determine the channel characteristics When the estimated channel parameter matrices are obtained, a recurrence formula can then be used to separate various speech signals including their reverberant counterparts As a finite impulse response (FIR) model is used to describe the observation model of the sources in the reverberant environment, it is not necessary for the processing speech signals to be uncorrelated Because it involves only simple computation, our approach can be used in online applications In this paper, we will investigate the validity of our algorithm and compare it with extended fourth-order blind identification (EFOBI) It is found that our method preserves both signal waveforms and their amplitudes even in a noisy environment, whereas EFOBI has not been able to achieve similar performance

A new algorithm on multiple unknown source signals estimation and separation in a reverberant space

Technologies for estimating talker location are applicable to teleconference systems with the sense of presence and security systems. Our proposed method estimates multiple talker locations by using synchronous multipliers; it was assumed that the microphones surrounded the talkers. This paper considers the situation in which the talkers surround the microphones. In this arrangement, the main problem is that the capacity for detecting talker location is decreased. Therefore, we propose a new method of subarray selection. Experiments show that the proposed method of subarray selection is effective in estimating talker location. © 2001 Scripta Technica, Electron Comm Jpn Pt 3, 84(9): 42–48, 2001

Estimation of multiple talker locations using randomly positioned microphones (method of subarray selection)

This paper proposes a method to estimate the waveform of sound sources. This is accomplished by using a microphone array where the microphones are not situated close to the sound sources. The waveform is estimated using the sound velocity and positions of the microphones and sound sources as the only fixed parameters. The positions of the sound sources can be estimated in advance by using a conventional method such as multiple signal classification method (MUSIC). An iteration method is introduced to reduce the effect of direct sounds and of significant image sources due to reflected noise and/or other sound sources, whose positions are known. Computer simulations and an experiment with loudspeakers were conducted to demonstrate the effectiveness of our method.

T. Sone

Papers

Estimation of the waveform of a sound source by using an iterative technique with many sensors