Helms Wells (closetcheck85)

9- and 16.9-dB improvements in SRTs for the beamformer and 3.5- and 12.3-dB improvements for triple beam (narrow and wide separations). Similar results were found for normal-hearing listeners presented with vocoded stimuli. Single beam improved speech-on-speech masking performance but yielded poor sound localization. Triple beam improved speech-on-speech masking performance, albeit less than the single beam, and sound localization. Thus, triple beam was the most versatile across multiple spatial-hearing domains.Little is known about the minimum sample length required for the stable acoustic assessment of speech in Parkinson's disease (PD). This study aimed to investigate the effect of the duration of the reading passage on the determination of reliable acoustic patterns in individuals with PD treated with subthalamic nucleus deep brain stimulation. A phonetically balanced reading text of 313 words was collected from 32 Czech persons with PD, and 32 age- and sex-matched healthy controls. The reading passage was segmented to produce ten sub-texts of increasing length ranging from a one- to a ten-segment-long sub-text. An error rate analysis was used to estimate the required stabilization value by evaluating the differences between the sub-texts and the entire text across seven hypokinetic dysarthria features. The minimum length of a reading passage equal to 128 words was found to be necessary for acoustic assessment, with similar lengths being required for the controls (120 words) and the two PD subgroups, including Parkinsonian individuals with a mild (126 words) and moderate (128 words) dysarthria severity. The current study provides important guidelines for the necessary sample length for future expert instrumental dysarthria assessments and assists in decreasing the time required for clinical speech evaluations.A decentralized method is proposed to estimate the two-dimensional horizontal ocean current field using the underwater acoustic sensor networks (UASNs), termed the "UASN-decentralized" method, which integrates the state-of-the-art ocean current field estimation techniques for UASNs triangle-division-based travel time difference tomography and a spatiotemporal autoregressive model of ocean current dynamics. Moreover, the UASN-decentralized method employs a single-time scale consensus+innovations distributed estimator, called the "distributed information Kalman filter," to perform decentralized estimation and tracking. Given the redundancy of travel time differences when using UASN-based tomography, sensor nodes are classified into two types (i.e., type I and type II) to perform different tasks to reduce computations. A shortest-path-based consensus weight matrix is designed to accommodate fast-varying ocean dynamics. More communication rounds after each sensing are studied as an extension of the adopted single-time scale distributed estimator. Synthetic data are used to verify the decentralized method. Monte Carlo simulations show the feasibility of the proposed method and its robustness to measurement error related problems. With an increased number of communication rounds, the proposed method can also work well for fast-varying dynamics or a lowered sensor measurement rate.Compressive beamforming has been successfully applied to direction-of-arrival estimation with sensor arrays. The results demonstrated that this technique achieves superior performance when compared with traditional high-resolution beamforming methods. The existing compressive beamforming methods use classical iterative optimization algorithms in their compressive sensing theories. However, the computational complexity of the existing compressive beamforming methods tend to be excessively high, which has limited the use of compressive beamforming in applications with limited computing resources. To address this issue, this paper proposes a fast compressive beamforming method which combines the shift-invariance of the array beam patterns with a fas