Acoustic filter-and-sum beamforming by adaptive principal component analysis - Warsitz, Ernst; Haeb-Umbach, Reinhold (IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005))
For human-machine interfaces in distant-talking environments multichannel signal processing is often employed to obtain an enhanced signal for subsequent processing. In this paper we propose a novel adaptation algorithm for a filter-and-sum beamformer to adjust the coefficients of FIR filters to changing acoustic room impulses, e.g. due to speaker movement. A deterministic and a stochastic gradient ascent algorithm are derived from a constrained optimization problem, which iteratively estimates the eigenvector corresponding to the largest eigenvalue of the cross power spectral density of the microphone signals. The method does not require an explicit estimation of the speaker location. The experimental results show fast adaptation and excellent robustness of the proposed algorithm.
Keywords: acoustic filter-and-sum beamforming; acoustic room impulses; acoustic signal processing; adaptive principal component analysis; adaptive signal processing; architectural acoustics; constrained optimization problem; cross power spectral density; deterministic algorithm; deterministic algorithms; distant-talking environments; eigenvalues and eigenfunctions; eigenvector; enhanced signal; filter-and-sum beamformer; FIR filter coefficients; FIR filter coefficients; FIR filters; gradient methods; human-machine interfaces; iterative estimation; iterative methods; largest eigenvalue; microphone signals; multichannel signal processing; optimisation; principal component analysis; spectral analysis; stochastic gradient ascent algorithm; stochastic processes

Robust speaker direction estimation with particle filtering - Warsitz, Ernst; Haeb-Umbach, Reinhold (IEEE Workshop on Multimedia Signal Processing (MMSP 2004))
The paper is concerned with binaural signal processing for a bimodal human-robot interface with hearing and vision. The two microphone signals are processed to obtain an enhanced single-channel input signal for the subsequent speech recognizer and to localize the acoustic source, an important information for establishing a natural human-robot communication. We utilize a robust adaptive algorithm for filter-and-sum beamforming (FSB) and extract speaker direction information from the resulting FIR filter coefficients. Further, particle filtering is applied which conducts a nonlinear Bayesian tracking of speaker movement. Good location accuracy can be achieved even in highly reverberant environments. The results obtained outperform the conventional generalized cross correlation (GCC) method.
Keywords: bimodal human-robot interface; binaural signal processing; enhanced single-channel input signal; filter-and-sum beamforming; filtering theory; FIR filter coefficient; generalized cross correlation method; microphones; microphone signal; nonlinear Bayesian tracking; particle filtering; robust adaptive algorithm; robust speaker direction estimation; signal processing; speech enhancement; speech recognition; speech recognizer; user interfaces