The results indicate that besides the specimen thickness, also the operator affects the absorption coefficient by a directional and non-random relationship. Hence, it needs to be controlled carefully. The method proves to be a promising pathway for knowledge discovery from acoustic measurement data using explainability approaches for machine learning models.Odontocetes produce ultrasonic clicks for navigation and foraging. These are commonly categorized as regular or buzz clicks based on the inter-click interval. Buzz clicks are linked to foraging behaviors and may be subdivided into slow buzz clicks for prey chase, and regular buzz clicks for prey capture. This study recorded these three click types produced by white-beaked dolphins (Lagenorhynchus albirostris) off the Northumberland coast, UK. Acoustic parameters (including duration, centroid frequency, and root-mean-squared bandwidth) were calculated and compared across the three click types. The results showed that the regular clicks had shorter durations and higher frequencies than both the buzz click types. The regular buzz clicks had longer durations, lower frequencies, and narrower bandwidths than the slow buzz clicks. Additionally, regardless of click type, about 30% of the clicks had high-frequency (200-250 kHz) secondary peaks and >90% of the clicks displayed spectral peak and notch patterns between 20 and 80 kHz. These findings are useful for future quantitative assessment of the echolocation performance of white-beaked dolphins in the wild. The patterns of spectral peaks and notches identified may facilitate for acoustic identification of this species.An analysis is presented of sound measurements performed near two detonations of unexploded ordnance (UXO) in the North Sea, at distances ranging from 1.5 to 12 km. The charge masses of the detonations were 325 and 140 kg TNT equivalent. The objective of the measurements was to improve the accuracy of model predictions of the area where UXO detonations affect harbour porpoises in the North Sea. For the predictions, an explosion emission model is combined with a shallow-water propagation model. The prediction model was previously validated for distances up to 2 km. The measurements reported here allowed validation up to a distance of 12 km. The measured levels and spectra are well explained by the model calculations. The model results depend strongly on the sea sediment layering. The propagation of high-frequency components appears to be affected primarily by the silty top layer, while low-frequency components are affected also by deeper sandy layers. Measured and calculated noise levels are used to determine permanent-threshold-shift effect distances for harbour porpoises (Phocoena phocoena). D-1553 nmr Values ranging from 2 to 6 km are found for the two detonations.A review of previous speech segmentation research suggests the prediction that listeners of Taiwanese Southern Min (TSM), a lexical tone language, would exploit vowel lengthening and syllable-onset consonant lengthening to locate word ends and beginnings, respectively. Yet, correlations between segment duration and tone identity in tone languages along with some TSM-specific phonological phenomena may work against such use. Two artificial language learning experiments examined TSM listeners’ use of the lengthening cues. The listeners heard the words of an artificial language (e.g., /ba.nu.me/) repeated continuously and identified them in a subsequent two-alternative forced-choice test. Experiment I revealed that their segmentation benefits from and only from word-initial onset lengthening or word-final vowel lengthening, supporting the prediction. Experiment II further demonstrated that these two cues in combination synergistically support segmentation at least when compared to word-initial onset lengthening alone, consistent with previous findings regarding complementary cues. These results furnish additional evidence that vowel and onset consonant lengthening affect segmentation in different ways, possibly reflecting a functional division between vowels and consonants that is supported by some prosody-computing mechanism. Additionally, vowel lengthening seems to affect segmentation to a greater extent than onset consonant lengthening. Possible explanations for this and further issues are discussed.The near and far fields of traditional loudspeakers are differentiated by whether the sound pressure amplitude is inversely proportional to the propagating distance. However, the audio sound field generated by a parametric array loudspeaker (PAL) is more complicated, and in this article it is proposed to be divided into three regions near field, Westervelt far field, and inverse-law far field. In the near field, the audio sound experiences strong local effects and an efficient quasilinear solution is presented. In the Westervelt far field, local effects are negligible so that the Westervelt equation is used, and in the inverse-law far field, a simpler solution is adopted. It is found that the boundary between the near and Westervelt far fields for audio sound lies at approximately a2/λ – λ/4, where a is transducer radius and λ is ultrasonic wavelength. At large transducer radii and high ultrasonic frequencies, the boundary moves close to the PAL and can be estimated by a closed-form formula. The inverse-law holds for audio sound in the inverse-law far field and is more than 10 meters away from the PAL in most cases. With the proposed classification, it is convenient to apply appropriate prediction models to different regions.In physical acoustic laboratories, wave propagation experiments often suffer from unwanted reflections at the boundaries of the experimental setup. We propose using multidimensional deconvolution (MDD) to post-process recorded experimental data such that the scattering imprint related to the domain boundary is completely removed and only the Green’s functions associated with a scattering object of interest are obtained. The application of the MDD method requires in/out wavefield separation of data recorded along a closed surface surrounding the object of interest, and we propose a decomposition method to separate such data for arbitrary curved surfaces. The MDD results consist of the Green’s functions between any pair of points on the closed recording surface, fully sampling the scattered field. We apply the MDD algorithm to post-process laboratory data acquired in a two-dimensional acoustic waveguide to characterize the wavefield scattering related to a rigid steel block while removing the scattering imprint of the domain boundary.