Bertelsenmalik9690

For both listener groups, the relative importance of the low-frequency bands increased under AV conditions, consistent with earlier studies using isolated speech bands. All three analyses showed similar results, indicating the absence of cross-band interactions. These results suggest that accurate prediction of AV speech intelligibility may require different frequency-importance functions than for AO conditions.Nowadays, wave-based simulations of head-related transfer functions (HRTFs) lack strong justifications to replace HRTF measurements. The main cause is the complex interactions between uncertainties and biases in both simulated and measured HRTFs. This paper deals with the validation of pinna-related high-frequency information in the ipsilateral directions-of-arrival, computed by lossless wave-based simulations with finite-difference models. A simpler yet related problem is given by the pinna-related transfer function (PRTF), which encodes the acoustical effects of only the external ear. Results stress that PRTF measurements are generally highly repeatable but not necessarily easily reproducible, leading to critical issues in terms of reliability for any ground truth condition. On the other hand, PRTF simulations exhibit an increasing uncertainty with frequency and grid-dependent frequency changes, which are here quantified analyzing the benefits in the use of a unique asymptotic solution. In this validation study, the employed finite-difference model accurately and reliably predict the PRTF magnitude mostly within ±1 dB up to ≈8 kHz and a space- and frequency-averaged spectral distortion within about 2 dB up to ≈ 18 kHz.The human phonation is characterized by periodical oscillations of the vocal folds with a complete glottis closure. In contrast, a glottal insufficiency (GI) represents an oscillation without glottis closure resulting in a breathy and weak voice. In this study, flow-induced oscillations of silicone vocal folds were modeled with and without glottis closure. The measurements comprised the flow pressure in the model, the generated sound, and the high-speed footage of the vocal fold motion. The analysis revealed that the sound signal for vocal fold oscillations without closure exhibits a lower number of harmonic tones with smaller amplitudes compared to the case with complete closure. The time series of the pressure signals showed small and periodical oscillations occurring less frequently and with smaller amplitude for the GI case. Accordingly, the pressure spectra include fewer harmonics similar to the sound. The analysis of the high-speed videos indicates that the strength of the pressure oscillations correlates with the divergence angle of the glottal duct during the closing motion. Physiologically, large divergence angles typically occur for a pronounced mucosal wave motion with glottis closure. Thus, the results indicate a correlation between the intensity of the mucosal wave and the development of harmonic tones.Natural soundscapes correspond to the acoustical patterns produced by biological and geophysical sound sources at different spatial and temporal scales for a given habitat. This pilot study aims to characterize the temporal-modulation information available to humans when perceiving variations in soundscapes within and across natural habitats. This is addressed by processing soundscapes from a previous study [Krause, Gage, and Joo. Selleckchem NMU chemical (2011). Landscape Ecol. 26, 1247] via models of human auditory processing extracting modulation at the output of cochlear filters. The soundscapes represent combinations of elevation, animal, and vegetation diversity in four habitats of the biosphere reserve in the Sequoia National Park (Sierra Nevada, USA). Bayesian statistical analysis and support vector machine classifiers indicate that (i) amplitude-modulation (AM) and frequency-modulation (FM) spectra distinguish the soundscapes associated with each habitat; and (ii) for each habitat, diurnal and seasonal variations are associated with salient changes in AM and FM cues at rates between about 1 and 100 Hz in the low (1-3 kHz) audio-frequency range. Support vector machine classifications further indicate that soundscape variations can be classified accurately based on these perceptually inspired representations.Array measurements can be contaminated by strong noise, especially when dealing with microphones located near or in a flow. The denoising of these measurements is crucial to allow efficient data analysis or source imaging. In this paper, a denoising approach based on a Probabilistic Factor Analysis is proposed. It relies on a decomposition of the measured cross-spectral matrix (CSM) using the inherent correlation structure of the acoustical field and of the flow-induced noise. This method is compared with three existing approaches, aiming at denoising the CSM, without any reference or background noise measurements and without any information about the sources of interest. All these methods make the assumption that the noise is statistically uncorrelated over the microphones, and only one of them significantly impairs the off-diagonal terms of the CSM. The main features of each method are first reviewed, and the performances of the methods are then evaluated by way of numerical simulations along with measurements in a closed-section wind tunnel.Understanding how sounds are perceived and interpreted is an important challenge for researchers dealing with auditory perception. The ecological approach to perception suggests that the salient perceptual information that enables an auditor to recognize events through sounds is contained in specific structures called invariants. Identifying such invariants is of interest from a fundamental point of view to better understand auditory perception and it is also useful to include perceptual considerations to model and control sounds. Among the different approaches used to identify perceptually relevant sound structures, vocal imitations are believed to bring a fresh perspective to the field. The main goal of this paper is to better understand how invariants are transmitted through vocal imitations. A sound corpus containing different types of known invariants obtained from an existing synthesizer was established. Participants took part in a test where they were asked to imitate the sound corpus. A continuous and sparse model adapted to the specificities of the vocal imitations was then developed and used to analyze the imitations.