Vladimir Tourbabin

Theoretical framework for the optimization of microphone array configuration for humanoid robot audition

An important aspect of a humanoid robot is audition. Previous work has presented robot systems capable of sound localization and source segregation based on microphone arrays with various configurations. However, no theoretical framework for the design of these arrays has been presented. In the current paper, a design framework is proposed based on a novel array quality measure. The measure is based on the effective rank of a matrix composed of the generalized head related transfer functions (GHRTFs) that account for microphone positions other than the ears. The measure is shown to be theoretically related to standard array performance measures such as beamforming robustness and DOA estimation accuracy. Then, the measure is applied to produce sample designs of microphone arrays. Their performance is investigated numerically, verifying the advantages of array design based on the proposed theoretical framework.

Optimal Real-Weighted Beamforming With Application to Linear and Spherical Arrays

One of the uses of sensor arrays is for spatial filtering or beamforming. Current digital signal processing methods facilitate complex-weighted beamforming, providing flexibility in array design. Previous studies proposed the use of real-valued beamforming weights, which although reduce flexibility in design, may provide a range of benefits, e.g., simplified beamformer implementation or efficient beamforming algorithms. This paper presents a new method for the design of arrays with real-valued weights, that achieve maximum directivity, providing closed-form solution to array weights. The method is studied for linear and spherical arrays, where it is shown that rigid spherical arrays are particularly suitable for real-weight designs as they do not suffer from grating lobes, a dominant feature in linear arrays with real weights. A simulation study is presented for linear and spherical arrays, along with an experimental investigation, validating the theoretical developments.

Enhanced robot audition by dynamic acoustic sensing in moving humanoids

Auditory systems of humanoid robots usually acquire the surrounding sound field by means of microphone arrays. These arrays can undergo motion related to the robots activity. The conventional approach to dealing with this motion is to stop the robot during sound acquisition. This approach avoids changing the positions of the microphones during the acquisition and reduces the robots ego-noise. However, stopping the robot can interfere with the naturalness of its behaviour. Moreover, the potential performance improvement due to motion of the sound acquiring system can not be attained. This potential is analysed in the current paper. The analysis considers two different types of motion: (i) rotation of the robots head and (ii) limb gestures. The study presented here combines both theoretical and numerical simulation approaches. The results show that rotation of the head improves the high-frequency performance of the microphone array positioned on the head of the robot. This is complemented by the limb gestures, which improve the low-frequency performance of the array positioned on the torso and limbs of the robot.

Direction of arrival estimation using microphone array processing for moving humanoid robots

The auditory system of humanoid robots has gained increased attention in recent years. This system typically acquires the surrounding sound field by means of a microphone array. Signals acquired by the array are then processed using various methods. One of the widely applied methods is direction of arrival estimation. The conventional direction of arrival estimation methods assume that the array is fixed at a given position during the estimation. However, this is not necessarily true for an array installed on a moving humanoid robot. The array motion, if not accounted for appropriately, can introduce a significant error in the estimated direction of arrival. The current paper presents a signal model that takes the motion into account. Based on this model, two processing methods are proposed. The first one compensates for the motion of the robot. The second method is applicable to periodic signals and utilizes the motion in order to enhance the performance to a level beyond that of a stationary array. Numerical simulations and an experimental study are provided, demonstrating that the motion compensation method almost eliminates the motion-related error. It is also demonstrated that by using the motion-based enhancement method it is possible to improve the direction of arrival estimation performance, as compared to that obtained when using a stationary array.

Speaker localization by humanoid robots in reverberant environments

One of the important tasks of a humanoid-robot auditory system is speaker localization. It is used for the construction of the surrounding acoustic scene and as an input for additional processing methods. Localization is usually required to operate indoors under high reverberation levels. Recently, an algorithm for speaker localization under these conditions was proposed. The algorithm uses a spherical microphone array and the processing is performed in the spherical harmonics domain, requiring a relatively large number of microphones to efficiently cover the entire frequency range of speech. However, the number of microphones in the auditory system of a humanoid robot is usually limited. The current paper proposes an improvement of the previously published algorithm. The improvement aims to overcome the frequency limitations imposed by the insufficient number of microphones. The improvement is achieved by using a novel space-domain distance algorithm that does not requires the transformation to the spherical harmonics domain, thereby avoiding the frequency range limitations. A numerical study shows two important results. The first is that, using the improved algorithm, the operation frequency range can be significantly extended. The second important result is related to the fact that higher frequencies contain more detailed information about the surrounding sound field. Hence, the additional higher frequencies lead to improved localization accuracy.

Utilizing motion in humanoid robots to enhance spatial information recordedby microphone arrays

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.

Objective measure for sound localization based on head-related transfer functions

Head-related transfer functions (HRTFs) are widely used in the study of the human auditory system. It is known that HRTFs contain spatial cues allowing individuals to localize sounds. Inter-aural phase and level differences, and high-frequency magnitude variations, are among the most common cues. While these cues require detailed analysis of specific HRTFs, in the current paper a new measure is proposed, based on the distribution of the singular values of the HRTF matrix, effectively representing the amount of information contained in the HRTFs as a function of frequency and arrival direction. This measure is generic, encompassing all cues in a single quantity. First, the validity of the proposed measure is justified theoretically. Then, the proposed measure is validated against empirically known results of human localization in the horizontal and median planes. The comparison is performed by taking into account two different aspects: (1) whether the information contained in the HRTFs is monaural or binaural, and (2) the variation of the minimum audible angle (MAA) and other localization measures as a function of azimuth and elevation. The results show that the proposed measure is in good agreement with the established theory of human sound localization and can be used as a predictor of the potential performance of human sound localization and of human-like systems such as humanoid robots.

Sub-Nyquist spatial sampling using arrays of directional microphones

Microphone arrays are commonly used for spatial filtering or beamforming. A variety of beamforming techniques offering high spatial resolution have been developed and are described in the literature. However, improved resolution may require an increase in the number of sensors and channels, resulting in complicated and expensive systems. In the current paper the use of arrays composed of directional sensors is proposed and the consequent benefit in terms of a reduction in the number of sensors is analyzed. It is shown that a reduction in the number of sensors can be achieved at the expense of reduced steering capabilities.

Theoretical framework for the design of microphone arrays for robot audition

An important part of a human-like robot is robot audition. Previous work presented systems capable of sound localization and source segregation based on microphone arrays of various configurations. However, no theoretical framework for assessing the quality of these array configurations has been presented. In the current paper such a measure is proposed based on the generalized HRTFs that account for microphone positions other than the ears. The measure is analyzed theoretically with respect to beamforming robustness and DOA estimation accuracy. The measure is then used to find the optimal location of a single microphone and a pair of microphones based on the generalized HRTF database obtained by means of BEM simulation. The results are not surprising, showing that the best position of a single microphone is the ear canal. For a pair of microphones, the results generally show that the sensors should be maximally spatially separated.

Electronic steering for a microphone array by sub-band phase compensation

Directional microphones are widely used in spatial filtering applications. The directivity and steering capabilities are usually realized using arrays of sensors connected to a digital processor. In general, these techniques are very complicated and expensive. In this work a continuous-time electronic steering technique for microphone array based on sub-band phase compensation is presented. It can be realized by means of analogue electronics, selecting gain and phase value for each sensor as a function of look direction. First, the spatial performance of the proposed microphone is analyzed at a single frequency. Then, the frequency range of interest is divided into several sub-bands according to the desired frequency resolution, and the weights are designed independently for each sub-band frequency. The paper presents a theoretical formulation of the proposed methods, and a numerical simulation showing that the performance of the proposed microphone is comparable to that of a conventional delay-and-sum beamformer.