Dual Microphone Sound Source Localization Using Reconfigurable Hardware
24 Mar 2017-Vol. 775, pp 397-406
TL;DR: An efficient reconfigurable hardware design of sound source localization system using one microphone pair using phase transform (PHAT) based filter using time delay of arrival (TDOA) algorithm to achieve time difference between the microphone signals is proposed.
Abstract: This paper proposes an efficient reconfigurable hardware design of sound source localization system using one microphone pair We have used time delay of arrival (TDOA) algorithm using phase transform (PHAT) to achieve time difference between the microphone signals Phased transform (PHAT) based filter can reach high SNR gains, which makes it very suitable for localizing the sound source in a microphone array system Our design has implemented on Spartan6 Lx45 FPGA and presented the implementation results in terms of accuracy and speech quality We compare the original angle between the microphones to the resultant angle between the microphones and observed that proposed design provides very sharp accuracy in every corresponding angle We also compare the speech quality of proposed design signal with normal delayed signal The evaluation infers that our proposed hardware induce feasible for hand-held devices
Citations
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16 Jan 2019-Microsystem Technologies-micro-and Nanosystems-information Storage and Processing Systems
TL;DR: The objective and subjective evaluation established that the proposed hardware provides better throughput compared to the existing state of the art research works and induces feasibility for hand-held devices in background noisy environment.
Abstract: This paper proposes an efficient reconfigurable hardware
design of dual microphone speech enhancement technique using sound source localization and multi band spectral subtraction methods with elimination of background noise. Firstly, we have used a time delay of arrival algorithm using phase transform (PHAT) to achieve the time difference between the microphone signals. PHAT based filter can reach high SNR gains, which makes it very suitable for localizing the sound source in a microphone array system. After adjustment of the delay between the signals, multi band spectral subtraction technique enhances the signal from the background noise environment in each of the frequency bands. Our design has been implemented in Spartan6 Lx45 FPGA and we have presented the implementation results in terms of subjective and objective evaluations. We have also compared the angular separation between the microphones to the resultant angle between the microphones and observed that proposed design provides very sharp accuracy in every corresponding angle. The objective and subjective evaluation established that our design provides better throughput compared to the existing state of the art research works. The evaluation infers that our proposed hardware induce feasibility for hand-held devices in background noisy environment.
3 citations
01 Jan 2019
TL;DR: The evaluation of the quality of speech of enhanced signal and its correctness of MAD to detect the single or dual microphone system implies that the proposed hardware can work as a proper embedded component for hardware-based execution for speech enhancement.
Abstract: In this paper, we have proposed field-programmable gate array (FPGA) based design and implementation of a novel speech enhancement system, which can work for a single microphone device as well as that of a dual microphone device providing background noise immunity. We proposed a microphone activity detector (MAD), which detects the presence of single or dual microphone scenario. After detecting the microphones, multiband spectral subtraction technique enhances the speech signal from different background noisy surrounds. We have implemented our proposed design in Spartan 6 LX45 FPGA using Xilinx system generator tools. The evaluation of the quality of speech of enhanced signal and its correctness of MAD to detect the single or dual microphone system implies that our proposed hardware can work as a proper embedded component for hardware-based execution for speech enhancement.
1 citations
References
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TL;DR: In this paper, a maximum likelihood estimator is developed for determining time delay between signals received at two spatially separated sensors in the presence of uncorrelated noise, where the role of the prefilters is to accentuate the signal passed to the correlator at frequencies for which the signal-to-noise (S/N) ratio is highest and suppress the noise power.
Abstract: A maximum likelihood (ML) estimator is developed for determining time delay between signals received at two spatially separated sensors in the presence of uncorrelated noise. This ML estimator can be realized as a pair of receiver prefilters followed by a cross correlator. The time argument at which the correlator achieves a maximum is the delay estimate. The ML estimator is compared with several other proposed processors of similar form. Under certain conditions the ML estimator is shown to be identical to one proposed by Hannan and Thomson [10] and MacDonald and Schultheiss [21]. Qualitatively, the role of the prefilters is to accentuate the signal passed to the correlator at frequencies for which the signal-to-noise (S/N) ratio is highest and, simultaneously, to suppress the noise power. The same type of prefiltering is provided by the generalized Eckart filter, which maximizes the S/N ratio of the correlator output. For low S/N ratio, the ML estimator is shown to be equivalent to Eckart prefiltering.
4,317 citations
TL;DR: A new approach is proposed that is based on eigenvalue decomposition that performs well and is very accurate for time delay estimation of acoustic source locations.
Abstract: To find the position of an acoustic source in a room, the relative delay between two (or more) microphone signals for the direct sound must be determined. The generalized cross-correlation method is the most popular technique to do so and is well explained in a landmark paper by Knapp and Carter. In this paper, a new approach is proposed that is based on eigenvalue decomposition. Indeed, the eigenvector corresponding to the minimum eigenvalue of the covariance matrix of the microphone signals contains the impulse responses between the source and the microphone signals (and therefore all the information we need for time delay estimation). In experiments, the proposed algorithm performs well and is very accurate.
395 citations
TL;DR: This paper addresses the specific application of source localization algorithms for estimating the position of speech sources in a real-room environment given limited computational resources and presents theoretical foundations of a speech source localization system.
332 citations
TL;DR: A novel sensor network source localization method based on acoustic energy measurements that makes use of the characteristics that the acoustic energy decays inversely with respect to the square of distance from the source is presented.
Abstract: A novel sensor network source localization method based on acoustic energy measurements is presented. This method makes use of the characteristics that the acoustic energy decays inversely with respect to the square of distance from the source. By comparing energy readings measured at surrounding acoustic sensors, the source location during that time interval can be accurately estimated as the intersection of multiple hyperspheres. Theoretical bounds on the number of sensors required to yield unique solution are derived. Extensive simulations have been conducted to characterize the performance of this method under various parameter perturbations and noise conditions. Potential advantages of this approach include low intersensor communication requirement, robustness with respect to parameter perturbations and measurement noise, and low-complexity implementation.
272 citations
TL;DR: Synthetic microphone signals generated with the image model technique are used to study the effects of room reverberation on the performance of the maximum likelihood estimator of the time delay, in which the estimate is obtained by maximizing the cross correlation between filtered versions of the microphone signals.
Abstract: Synthetic microphone signals generated with the image model technique are used to study the effects of room reverberation on the performance of the maximum likelihood (ML) estimator of the time delay, in which the estimate is obtained by maximizing the cross correlation between filtered versions of the microphone signals. The results underscore the adverse effects of reverberation on the bias, variance and probability of anomaly of the ML estimator. Explanations of these effects are provided.
189 citations