ABSTRACT
Multiparametric indices offer a more comprehensive approach to voice quality assessment by taking into account multiple acoustic parameters. Artificial intelligence technology can be utilized in healthcare to evaluate data and optimize decision-making processes. Mobile devices provide new opportunities for remote speech monitoring, allowing the use of basic mobile devices as screening tools for the early identification and treatment of voice disorders. However, it is necessary to demonstrate equivalence between mobile device signals and gold standard microphone preamplifiers. Despite the increased use and availability of technology, there is still a lack of understanding of the impact of physiological, speech/language, and cultural factors on voice assessment. Challenges to research include accounting for organic speech-related covariables, such as differences in conversing voice sound pressure level (SPL) and fundamental frequency (f0), recognizing the link between sensory and experimental acoustic outcomes, and obtaining a large dataset to understand regular variation between and within voice-disordered individuals. Our study investigated the use of cellphones to estimate the Acoustic Voice Quality Index (AVQI) in a typical clinical setting using a Pareto-optimized approach in the signal processing path. We found that there was a strong correlation between AVQI results obtained from different smartphones and a studio microphone, with no significant differences in mean AVQI scores between different smartphones. The diagnostic accuracy of different smartphones was comparable to that of a professional microphone, with optimal AVQI cut-off values that can effectively distinguish between normal and pathological voice for each smartphone used in the study. All devices met the proposed 0.8 AUC threshold and demonstrated an acceptable Youden index value.
ABSTRACT
Whale-watching vessels contribute to elevated ambient sound levels in marine habitats. The reduction in maritime tourism activities during the Covid-19 pandemic provided an unprecedented opportunity to study the acoustic response of marine mammals to noise associated with whale-watching activities. In this study, we used acoustic recordings, visual observations, and Automatic Identification System data to determine the changes in humpback whale Megaptera novaeangliae calling behavior associated with whale-watching vessels on a foraging ground in Skjálfandi Bay, Iceland. We compared pre-pandemic summer months (2018) with pandemic (2020) conditions to quantify reductions in vessel activity and determine changes in calling behavior. Broadband ambient sound pressure levels were low in both years (median ~90 dBRMS (25-1300 Hz) re 1 µPa). During the Covid-19 pandemic (2020), the number of whale-watching trips was reduced by 68.6%. The number of humpback whale call detections increased nearly 2-fold. Ambient sound pressure levels stayed the same. We found that humpback whales reduce their calling effort in the presence of vessel sound independent of the overall ambient sound. As whale-watching vessel traffic rebounds and continues to grow, demonstrating behavioral responses should inform management plans such as vessel codes of conduct and marine spatial planning.
ABSTRACT
The arrangement of natural and physical features on the earth's surface are a few among the countless items that govern the airborne acoustic transmission at boundary layers. In particular, if the acoustic waves are attributes of live concerts at open-air theatres, without losing the sheen and quality, the audience should certainly receive the unbroken depth of the performance. Hence, at all times, it is advisable to analyse the auditory receptiveness, particularly in all intended recreational spaces. The current pandemic circumstances and the mandated COVID-19 prevention protocols encourage gatherings in naturally ventilated outdoor regions than confined indoors. This work predicts and quantifies the acoustic experience at the naturally carved amphitheatre at SAINTGITS, an autonomous institution at the down South-West of the Indian Subcontinent. The entire recreational space at SAINTGITS AMPHI was separately modelled as a Base case and Advanced case, and were analysed using the acoustic modelling module of EASE Focus, a renowned simulation freeware, which is in strict adherence with the International standards. The variation in loudness received at the nearest and farthest ends of the amphitheatre was between 67 to 80 dB. Though the Zero frequency SPL (Z-weighting) exhibited the loudness in the range of 81 to 85 dB and could maintain a safer auditory level for any human ear, it was confined to a hemispherical region near the sound source. A vertical beam angle of -4.0 degrees was found to be effective throughout. The procedures and analyses will certainly help the future organizers and stakeholders to effectively plan the resources to reap rich acoustic experience at terrain-centric locales. The surface topography and contours were plotted with another set of freeware, the CADMAPPER and the QUIKGRID, to compare terrain gradient with the known data. Furthermore, this interdisciplinary research exhibits the extensive simulation capability of both EASE Focus and QUIKGRID and demonstrates the modelling versatility and deliverable potential of these freeware to benefit the budding architects and researchers.
ABSTRACT
Headsets are increasingly used in the working environment. In addition to being frequently used by call-centre staff, they are also becoming more popular with remote workers and teleconference participants. The aim of this work was to describe and evaluate the acoustic signal parameters reproduced by headsets and examine the factors affecting the values of these parameters. The tests were carried out in laboratory conditions using a manikin (head and torso simulator) designed for acoustic research. A total of 12 headset models were tested during the research. The results show that the A-weighted sound pressure level of the test signal reproduced by four (100% gain) and two (75% gain) headsets exceeded 85 dB. The highest equivalent A-weighted sound pressure level was 92.5 dB, which means that the headset should not be used for more than approx. 1 h and 25 min; otherwise, the criterion value will be exceeded. The analysis of the acoustic signal reproduced by the headsets confirmed that the A-weighted sound pressure level affected the gain level in the test signal reproduction path. This value also depended on the type of connector used, the computer from which the test signal was reproduced and the type of sound card used.