Radial Filter Design Using Kaiser Window Polynomials for Speech Source Separation

Radial filter design for processing near field speech sources over a spherical microphone array is challenging. Polynomial based radial filter design procedures have been proposed in earlier work. In this paper we address the issue of radial filter design using a family of orthogonal polynomials called the Gegenbauer polynomials. The radial filters designed using this approach indicate an improved radial response and greater efficiency in attenuating distant sources. Improved white noise gain and directivity index are also noted from experimental evaluations. The radial filters hence designed are used to separate directionally co-incident near field speech sources. Subjective evaluation is conducted on separated sources using measures like LSD, PESQ, and SDR. The subjective evaluation scores are motivating enough to be considered for practical speech and audio applications.

When close enough to a microphone array, the spherical nature of radiating sources allows for sound field processing in terms of distance as well as direction. As part of an on-going study on beamforming given sources close to a spherical microphone array, sound field processing is examined through the use of radial filters. In this paper, a radial Dolph-Chebyshev design is presented for attenuating far-field interference given sources close to the array surface. The proposed radial filter facilitates an analytical formulation of the design technique, and may be practical for sources very close to the array surface.

Fractional Fourier transform (FRFT) is generalization of Fourier transform. It has an adjustable parameter in the form of $$\alpha$$ rotational angle that makes it more useful in the various fields of science and engineering. In this paper, an analysis of Kaiser and Gaussian window functions is obtained in the FRFT domain. The behavior of these window functions is observed in terms of spectral parameters along with their special cases. The effect of their behavior is applied in FIR filter implementation and tunes its transition band. By changing the order of the FRFT, the variation in the transition width of windowed FIR filter is obtained which makes it possible to vary the stop-band attenuation. While designing a new filter, this tuning method saves significant time to compute filter coefficients. To validate the results, tuning of the FIR filter with Gaussian and Kaiser window functions is achieved in FRFT domain and the performance of the filter is measured in terms of stop-band attenuation.

Low-pass filtering of sinograms in the radial direction is the most common practice to limit noise amplification in filtered back projection (FBP) reconstruction of positron emission tomography studies. Other filtering strategies have been proposed to prevent the loss in resolution due to low-pass radial filters, although results have been diverse. Using the well-known properties of the Fourier transform of a sinogram, the authors defined a binary mask that matches the expected shape of the support region in the Fourier domain of the sinogram ("bow tie"). This mask was smoothed by a convolution with a ten-point Gaussian kernel which not only avoids ringing but also introduces a pre-emphasis at low frequencies. A new filtering scheme for FBP is proposed, comprising this smoothed bow-tie filter combined with a standard radial filter and an axial filter. The authors compared the performance of the bow-tie filtering scheme with that of other previously reported methods: Standard radial filtering, angular filtering, and stackgram-domain filtering. All the quantitative data in the comparisons refer to a baseline reconstruction using a ramp filter only. When using the smallest size of the Gaussian kernel in the stackgram domain, the authors achieved a noise reduction of 33% at the cost of degrading radial and tangential resolutions (14.5% and 16%, respectively, for cubic interpolation). To reduce the noise by 30%, the angular filter produced a larger degradation of contrast (3%) and tangential resolution (46% at 10 mm from the center of the field of view) and showed noticeable artifacts in the form of circular blurring dependent on the distance to the center of the field of view. For a similar noise reduction (33%), the proposed bow-tie filtering scheme yielded optimum results in resolution (gain in radial resolution of 10%) and contrast (1% increase) when compared with any of the other filters alone. Experiments with rodent images showed noticeable image quality enhancement when using the proposed bow-tie filtering scheme.

This paper concerns the problem of convolutive sound source separation from mutlichannel recordings made with a spherical microphone array. In particular, we formulate two state-of-the-art separation techniques based on Expectation Maximization (EM) and Nonnegative Tensor Factorization (NTF) in the spherical harmonic domain (SHD). Furthermore, we adjust and incorporate the Gaussian Localization Prior (GLP) to the proposed algorithms, which yields two variants of the derived methods. For the source signal reconstruction, a Minimum Variance Distortionless Response (MVDR) beamformer with a single-channel Wiener post-filter is employed. The performance comparison is based on experimental evaluation using micro-phone signals simulated with the image-source method in several scenarios, including diverse geometrical setup, different number of sources and various types of source signals, namely the recordings of speech utterances and musical instruments. The experimental results for the first-order ambisonic signals show that the proposed methods enable high-quality sound source separation in the spherical harmonic domain. In particular, we show that incorporation of the Gaussian Localization Prior to the proposed algorithms leads to a substantial improvement in separation performance.

One of the most major trends in modern microwave signals is the shift toward wider bandwidths. Analog wideband receiver designs can provide accommodation of the technology-stressing bandwidths, but come up to a cost of reduced flexibility. Digital approaches, alternatively, provide flexibility in receiver signal processing, but they are limited by analog-to-digital converter resolution and power consumption. In this paper, design and implementation of a 1-GHz signal bandwidth digital receiver, which uses the Kaiser window function and compensation technique, is presented. The Kaiser window reduces the spectral leakage by eliminating the discontinuities at the time window edges and the compensation uncovers the weak signal for extension of the two-signal spurious-free dynamic range (SFDR) of the receiver. The combination of both techniques extends the two-signal SFDR of the receiver to 24 dB. A novel hardware implementation of the Kaiser window and the compensation method is presented

This paper utilizes a rigid spherical microphone array to reduce wind noise. In the experiments conducted, a loudspeaker is used to reproduce the desired sound signal and an axial fan is employed to generate wind noise in an anechoic chamber. The sound signal and wind noise are measured separately with the spherical microphone array and analyzed in the spherical harmonic domain. The wind noise is found to be irregularly distributed in the spherical harmonic domain, distinct from the sound signal which is concentrated in the first few spherical harmonic modes. This difference is utilized to reduce wind noise without degrading the desired sound pressure level (SPL) by use of a low pass filter method in the spherical harmonic domain. Experimental results with both single-tonal and multi-tonal sound signals demonstrate that the proposed method can reduce wind noise by more than 10 dB in the frequency range below 500 Hz. The SPL of the desired sound signal can be extracted from wind noise with an error within 1.0 dB, even when the sound level is 8 dB lower than wind noise.

Digital filter plays an important role in the advanced era of communication system. Digital filters basically provide high attenuation to the unwanted ones and offer very low or ideally zero attenuation to desired signal components when its impulse response is adjusted as per requirement. But the design of a digital filter satisfying all the required conditions is a challenging task. In this paper, design techniques of low pass FIR filters using Tukey window, Kaiser Window, and Gaussian window methods are presented. The magnitude and phase responses are demonstrated in the simulation section for the different design techniques of digital low pass FIR filters. From the simulation results, it is observed that for a longer length the FIR filter has a sharper cut-off FIR filter and a narrow transition band.

Spherical array plays important role in 3D targets localization. In this paper, we develop a novel DOA estimation method for the spherical array with super resolution approach. The proposed method operates in spherical harmonic domain. Based on the atomic norm minimization, we develop a gridless L1-SVD algorithm in spherical harmonic domain and then we adopt the spherical ESPRIT method to two-dimensional DOA estimation. Compared to the previous work, the proposed method acquires better estimation performance. Numerical simulation results verify the performance of the proposed method.

A recent and fast evolving application for microphone arrays is the auditory systems of humanoid robots. These arrays, in contrast to conventional arrays, are not fixed in a given position, but move together with the robot. While imposing a challenge to most conventional array processing algorithms, this movement offers an opportunity to enhance performance if utilized in an appropriate manner. The array movement can increase the amount of information gathered and, therefore, improve various aspects of array processing. This paper presents a theoretical framework for the processing of moving microphone arrays for humanoid robot audition based on a representation of the surrounding sound field in the spherical harmonics domain. A simulation study is provided, illustrating the use and the potential advantage of the proposed framework.

This study examines a compressive spherical beamforming (CSB) method, using a rigid spherical microphone array to localize and quantify the acoustic contribution of sources. The method relies on the array signal model in the spherical harmonics domain that can be represented as a spatially sparse problem. This makes it possible to use compressive sensing to solve an underdetermined problem via promoting sparsity. The estimation of the angular position of sources with respect to the microphone array, as well as the three-dimensional localization over a volume are investigated. Several sparse recovery algorithms [orthogonal matching pursuit (OMP), generalized OMP, ϱ1-norm minimization, and reweighted ϱ1-norm minimization] are examined for this purpose. The numerical and experimental results indicate that sparse recovery methods outperform conventional spherical harmonics beamforming. Reweighted ϱ1-norm has good adaptability to noise, improving the robustness of CSB. The method can successfully localize the angular position of sources, and quantify their relative pressure contribution. The method is promising to localize sources in a three-dimensional domain of interest. However, the three-dimensional localization is more sensitive to noise, source distance, and properties of the sensing matrix than the two-dimensional localization.

The reliable estimation of fiber orientation distributions from diffusion-sensitized magnetic resonance imaging is an important processing step for revealing structural connectivity in the human brain. Fiber orientation distributions are usually represented in spherical harmonic (SH) domain, but many modern spatial regularization techniques were not yet formulated in SH-domain such that they cannot benefit from the well known advantages. In this article we propose a novel SH-formulation of the contour enhancement propagator (fiber continuity) which enables to implement a variety of processing steps in SH-domain.

Multiband phased array antennas are required for today's multi-function communication applications. These types of antennas play a major role where space is limited. A Koch array antenna is capable of covering several different frequency bands. Koch arrays can be used to obtain multiband behaviour in which side-lobe ratio and radiation pattern characteristics are held same at several frequency bands. In this paper a technique is introduced for synthesizing fractal radiation patterns using Kaiser Window functions. This can lead to thinned multiband array of minimal physical size. This method includes the change of parameters of Kaiser Window by which other windows like Rectangular, Bartlett, Hamming, Blackman and Hanning windows are generated. This paper compares the performance of reduced Koch arrays for multiband operation.

Open-sphere microphone arrays are preferred over rigid-sphere arrays when minimal interaction between array and the measured sound field is required. However, open-sphere arrays suffer from poor robustness at null frequencies of the spherical Bessel function. This letter proposes a maximum likelihood method for direction of arrival estimation in the spherical harmonic domain, which avoids the division of the spherical Bessel function and can be used at arbitrary frequencies. Furthermore, the method can be easily extended to wideband implementation. Simulation and experiment results demonstrate the superiority of the proposed method over the commonly used methods in open-sphere configurations.

Source localization has been studied in the spatial domain using differential geometry in earlier work. However, parameters of the sensor array manifold have hitherto not been investigated for source localization in spherical harmonics domain. The objective of this work is to represent and model the manifold surface using differential geometry. The system model for source localization over a spherical harmonic manifold is first formulated. Subsequently, the manifold parameters are modeled in the spherical harmonics domain. Source localization methods using MUSIC and MVDR over the spherical harmonics manifold are developed. Experiments on source localization using a spherical microphone array indicate high resolution in noise.