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Time Scale Modification (TSM) is a well-researched field; however, no effective objective measure of quality exists. This paper details the creation, subjective evaluation, and analysis of a dataset for use in the development of an objective measure of quality for TSM. Comprised of two parts, the training component contains 88 source files processed using six TSM methods at 10 time scales, while the testing component contains 20 source files processed using three additional methods at four time scales. The source material contains speech, solo harmonic and percussive instruments, sound effects, and a range of music genres. Ratings (42 529) were collected from 633 sessions using laboratory and remote collection methods. Analysis of results shows no correlation between age and quality of rating; expert and non-expert listeners to be equivalent; minor differences between participants with and without hearing issues; and minimal differences between testing modalities. A comparison of published objective measures and subjective scores shows the objective measures to be poor indicators of subjective quality. Initial results for a retrained objective measure of quality are presented with results approaching average root mean squared error loss and Pearson correlation values of subjective sessions. The labeled dataset is available at http//ieee-dataport.org/1987.A lifetime ago, as an undergraduate, I joined a team that developed a new way of thinking about the sensitivity of sensory systems. My teammates were Wilson (Spike) Tanner and John Swets, both now deceased, and we were working at the University of Michigan. I also wish to thank J.C.R. Licklider, J. P. Egan, and Lloyd Jeffress who aided and encouraged that development. I am gratified that what came to be called signal-detection theory (SDT) was so widely accepted and its methods so widely adopted. However, I am somewhat disappointed about how SDT commonly is portrayed, and taught. My reasons are presented here.Around 35 000 km high-speed railways are in operation in China with a maximum speed of 350 km/h. selleck chemicals llc The main track form on the high-speed lines is non-ballasted slab track. Measurements show that, at high speeds, rolling noise is still the dominant source for both interior and exterior noise. Although rolling noise modelling has been investigated for more than 30 years, a train running at 350 km/h or higher along a non-ballasted slab track introduces a number of new factors which have not been adequately addressed in the past. The aim of this paper is to describe an approach that brings together elements that have been developed recently to model rolling noise for a high-speed train running on a slab track. Features of the approach include modelling interactions between multiple moving and rotating wheelsets with an infinitely long periodic track, treating all the radiators as moving sources, and directly predicting sound pressure frequency spectra for observation points near the track. Results are produced for a typical Chinese high-speed train and track, including wheel and rail receptances, wheel/rail forces, comparison of rolling noise with measured pass-by noise, dependence on train speed, and contributions from the wheelset, rail, and slab.The problem of estimating spatial distribution and density of vocalizing marine animals is addressed. The proposed solution is based on using a fixed compact array of synchronized hydrophones and statistically optimal detection and estimation algorithms. The closed-form representations of the practical algorithms are presented. The performance of the proposed technique is evaluated analytically and using statistical simulations. The case study involved identifying an area of high residency and estimating the density of vocalizing beluga whales in the St. Lawrence Estuary. The advantages and disadvantages of the proposed technique are demonstrated and the future steps are discussed.For an acoustic receiver deployed at the bottom of the direct arrival zone of a submerged source at short horizontal ranges in deep ocean, the interference pattern of the direct and surface-reflected acoustic arrivals shows periodic modulation, which is directly related to the source depth, source frequency, and vertical arrival angle. In this work, the interference cycle presented in the frequency domain is used to extract the broadband source depth, with the vertical arrival angle obtained from the ratio of vertical acoustic intensity and horizontal acoustic intensity from the signal recorded by a single vector sensor. Experimental results demonstrate the source depth estimation without requiring knowledge of the ocean environment.This study analyzed the durational and spectral differences and their interaction in the production of seven German tense-lax vowel pairs between 30 German native speakers and 30 Mandarin learners of German. The results showed that Mandarin speakers differed significantly from the German speakers in producing the German tense-lax contrast. The general pattern was that Mandarin learners employed temporal features more strongly than spectral features to indicate the tense-lax contrast as compared to German speakers. The phonetic influences of the Mandarin language on the production of German tense and lax vowels are discussed.This study compares event-related potentials (ERPs) elicited by variations of sound location in free and reverberant fields. The virtual sound sources located at azimuths 0°-40° were synthesized with head-related transfer functions and binaural room impulse responses for free and reverberant fields, respectively. The sound stimulus at 0° was assigned as standard in the oddball paradigm. Results show that the P3 amplitude is larger in the free field and acoustical conditions have no significant effect on the amplitudes of N2 and mismatch negativity. Moreover, a linear relationship between sound angle and amplitude of ERP components is observed.This work presents a two-microphone speech enhancement (SE) framework based on basic recurrent neural network (RNN) cell. The proposed method operates in real-time, improving the speech quality and intelligibility in noisy environments. The RNN model trained using a simple feature set-real and imaginary parts of the short-time Fourier transform (STFT) are computationally efficient with a minimal input-output processing delay. The proposed algorithm can be used in any stand-alone platform such as a smartphone using its two inbuilt microphones. The detailed operation of the real-time implementation on the smartphone is presented. The developed application works as an assistive tool for hearing aid devices (HADs). Speech quality and intelligibility test results are used to compare the proposed algorithm to existing conventional and neural network-based SE methods. Subjective and objective scores show the superior performance of the developed method over several conventional methods in different noise conditions and low signal to noise ratios (SNRs).

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