Acoustic Loudness Research Articles

The Mitigating Effects of Water Sound Attributes on Stress Responses to Traffic Noise

Traffic noise is a significant risk factor for adverse health outcomes. Despite burgeoning interest in reducing the harmful health effects of traffic noise, research on the influence of physical and psychoacoustic attributes has been sparse. Consequently, this study examines the impacts of various acoustic attributes on mitigating stress response to traffic noise using dependent variables derived from electrodermal activity. The results indicate that: (a) mixing water sound (noise) at a low signal-to-noise ratio effectively mitigated stress response to traffic noise (signal), whereas mixing white noise with high fractal complexity (noise) significantly induced stress; and (b) sound pressure and acoustic sharpness significantly reduced stress response to traffic noise. Conversely, attributes such as high fractal complexity, moderate and high signal-to-noise ratios, acoustic loudness, and mean frequency significantly increased stress. This research offers a viable blueprint for creating evidence-based noise mitigation strategies that focus on intervention sound attributes.

“Musicalization of the Culture”: Is Music Becoming Louder, More Repetitive, Monotonous and Simpler?

“Musicalization of the culture” is the social science concept proposed by American philosopher George Stainer. He depicted the glooming future of music—it would become omnipresent while having increasing volume, repetitiveness, and monotony, which are ascribed to the debase of literal aesthetics. Although research that relates to one or some of these predictions exists, neither of them encompass all these “musicalization” manifestations, nor do they study the trend of these predictions over time. Therefore, this preliminary research tries to validate whether music has gained acoustic loudness, and lyrical repetitiveness, monotony, and simplicity in a computational fashion. Conducting time-series analysis with trend detection, we confirmed the increasing trends of acoustic loudness and repetitiveness but not monotony and simplicity from 1970 to 2016 using the MetroLyrics dataset and Spotify API. To investigate the simultaneity of these trends, we further conducted synchrony analysis and found little evidence indicating they would influence each other in a lagged fashion. In light of the results, we briefly discussed our findings by relating to the music industry change in reality. Our research made the first attempt to answer this music sociological preposition. On top of this, we also proposed novel metrics to quantify repetitiveness using closed frequent sequential pattern mining, which could be illuminating for future research.

“Musicalization of the Culture”: Is Music Becoming Louder, More Repetitive, Monotonous and Simpler?

“Musicalization of the culture” is the social science concept proposed by American philosopher George Stainer. He depicted the glooming future of music—it would become omnipresent while having increasing volume, repetitiveness, and monotony, which are ascribed to the debase of literal aesthetics. Although research that relates to one or some of these predictions exists, neither of them encompass all these “musicalization” manifestations, nor do they study the trend of these predictions over time. Therefore, this preliminary research tries to validate whether music has gained acoustic loudness, and lyrical repetitiveness, monotony, and simplicity in a computational fashion. Conducting time-series analysis with trend detection, we confirmed the increasing trends of acoustic loudness and repetitiveness but not monotony and simplicity from 1970 to 2016 using the MetroLyrics dataset and Spotify API. To investigate the simultaneity of these trends, we further conducted synchrony analysis and found little evidence indicating they would influence each other in a lagged fashion. In light of the results, we briefly discussed our findings by relating to the music industry change in reality. Our research made the first attempt to answer this music sociological preposition. On top of this, we also proposed novel metrics to quantify repetitiveness using closed frequent sequential pattern mining, which could be illuminating for future research.

Categorical loudness scaling in cochlear implant recipients

Objective: This study investigated categorical loudness scaling in a large group of cochlear implant (CI) recipients. Design: Categorical loudness was measured for individually determined sets of current amplitudes on apical, mid and basal electrodes of the Nucleus array. Study sample: Thirty adult subjects implanted with the Nucleus CI. Results: Subjects were generally reliable in categorical loudness scaling. As expected, current levels eliciting the same loudness categories differed across subjects and electrodes in many cases. After scaling the electric levels to remove differences in dynamic ranges across subjects and electrodes, the across-subject loudness functions for the three electrodes were very similar. Conclusions: Scaled electric current to remove differences in dynamic range, as implemented in the Nucleus processor, ensures uniform loudness across the array and CI recipients. The results also showed that categorical loudness scaling for electric stimulation was similar to that for acoustic stimulation in normal hearing subjects. These findings could be used as a guide for aligning electric and acoustic loudness in CI recipients with contralateral hearing.

Development of a loudness normalisation strategy for combined cochlear implant and acoustic stimulation

Users of a cochlear implant together with a hearing aid in the non-implanted ear currently use devices that were developed separately and are often fitted separately. This results in very different growth of loudness with level in the two ears, potentially leading to decreased wearing comfort and suboptimal perception of interaural level differences. A loudness equalisation strategy, named ‘SCORE bimodal’, is proposed. It equalises loudness growth for the two modalities using existing models of loudness for acoustic and electric stimulation, and is suitable for implementation in wearable devices. Loudness balancing experiments were performed with six bimodal listeners to validate the strategy. In a first set of experiments, the function of each loudness model used was validated by balancing the loudness of four harmonic complexes of different bandwidths, ranging from 200 Hz to 1000 Hz, separately for each ear. Both the electric and acoustic loudness models predicted the data well. In a second set of experiments, binaural balancing was done for the same stimuli. It was found that SCORE significantly improved binaural balance.

Application of Real-Time Loudness Models Can Improve Speech Recognition for Cochlear Implant Users

The aim of cochlear implant (CI) stimulation strategies is to appropriately encode the important aspects of sound into a pattern of electrical stimulation. Recent research using numerical models of loudness perception has identified that there are large differences between how loudness is encoded by existing CI sound-processing strategies and how loudness is experienced by normally hearing listeners. In this paper, we present a new CI sound-coding algorithm aimed at addressing these discrepancies. This strategy, named SCORE, uses models of electric and acoustic loudness to modify the output of an existing CI sound-processing scheme in real time, so that the loudness changes are more accurately represented in the patterns of electrical stimulation. Five subjects (six implanted ears) were tested for understanding of speech presented at relatively low levels in quiet conditions. Using SCORE, subjects demonstrated an average 8.8 percentage-point statistically significant improvement in the number of words correctly identified relative to ACE, a commonly used stimulation strategy. These findings show that loudness changes over time are important for speech intelligibility, and that improving loudness coding in existing CI devices may lead to perceptual benefits.

Sound-processing strategy for cochlear implants

A sound processing method for auditory prostheses, such as cochlear implants, which is adapted to improve the perception of loudness by users, and to improve speech perception. The overall contribution of stimuli to simulated loudness is compared with an estimate of acoustic loudness for a normally hearing listener based on the input sound signal. A weighting is applied to the filter channels to emphasize those frequencies which are most important to speech perception for normal hearing listeners when selecting channels as a basis for stimulation.

Speech perception with a cochlear implant sound processor incorporating loudness models

Recently, a new paradigm for processing sounds for cochlear implants has been described that aims to normalize loudness for complex signals, relative to normal acoustic loudness perception [McDermott et al., J. Acoust. Soc. Am. 114, 2190–2197 (2003)]. A first implementation of a sound processor based on this paradigm, called SpeL, has been evaluated with speech perception tests conducted in quiet and in noise. For the five participating subjects, the average scores from these tests for SpeL were very close to those for the conventional ACE scheme. However, audibility was improved by about 5 dB for SpeL compared with ACE.

Monaural and binaural loudness measures in cochlear implant users with contralateral residual hearing.

The aim was to measure the loudness of monaural and binaural stimuli in a group of cochlear implant users who had residual hearing in the nonimplanted ear, and to consider the implications of these measures for a binaural fitting consisting of a hearing aid and an implant in opposite ears. Three independent hypotheses were addressed: that the shapes of the electric and acoustic loudness growth functions would be similar, although the dynamic ranges would differ; that standard implant and hearing aid fittings would result in substantial loudness mismatches between the acoustic and electric signals; and that loudness summation would occur for binaural combinations of electric and acoustic signals. A modified version of the "Loudness Growth in 1/2-Octave Bands" method (Allen, Hall, & Jeng, 1990) was used to measure loudness growth for each ear of nine subjects. At the time of the experiment, the subject group included all implant users in Melbourne and Denver who were available for research and who also had sufficient residual hearing to use a hearing aid in the nonimplanted ear. Five acoustic frequencies and five electrodes were measured for each subject. The same subjects also estimated the loudness of a set of stimuli including monaural and binaural signals chosen to cover the loudness range from very soft to loud. The shapes of the averaged loudness growth functions were similar in impaired and electrically stimulated ears, although the shapes of iso-loudness curves were quite different in the two ears, and dynamic ranges varied considerably. Calculations based on the psychophysical data demonstrated that standard fitting procedures for cochlear implants and hearing aids lead to a complex pattern of loudness differences between the ears. A substantial amount of loudness summation was observed for the binaural stimuli, with most summation occurring when the acoustic and electric components were of equal loudness. This is consistent with observations for subjects with normal hearing and subjects with bilaterally impaired hearing. These experiments provide data on which criteria and methods for the binaural fitting of cochlear implants and hearing aids may be based. It is unlikely that standard monaural fitting methods for cochlear implants and hearing aids will result in balanced loudness between the two ears across a reasonably broad range of frequencies and levels. It is also likely that output levels of both devices will need to be reduced relative to a monaural fitting to compensate for the binaural summation of loudness in some listeners.