Acoustics@Home: Laboratories and student-led projects conducted for an undergraduate engineering experimentation course during the COVID-19 pandemic.

Hands-on, project-based learning was difficult to achieve in online classes during the COVID-19 pandemic. The Engineering Experimentation course at Cooper Union teaches third-year mechanical engineering students practical experimental skills to measure physical phenomenon, which typically requires in-person laboratory classes. In response to COVID, a low-cost, at-home laboratory kit was devised to give students tools to conduct experiments. The kit included a microcontroller acting as a data-acquisition device and custom software to facilitate data transfer. A speed of sound laboratory was designed with the kit to teach skills in data collection, signal processing, and error analysis. The students derived the sound speed by placing two microphones a known distance apart and measuring the time for an impulsive signal to travel from one to the other. The students reported sound speeds from 180.7-477.8 m/s in a temperature range from 273.7-315.9 K. While these reported speeds contained a large amount of error, the exercise allowed the students to learn how to account for sources of error within experiments. This paper also presents final projects designed by the students at home, an impedance tube and two Doppler shift experiments, that exhibit successful and effective low-cost solutions to demonstrate and measure acoustic phenomenon.

Sensitivity of the human auditory cortex and reward network to reverberant musical stimuli.

A room's acoustics can alter subjective impressions of music, including preference. However, little research has characterized the brain's response to room conditions. Functional magnetic resonance imaging (fMRI) was used to investigate the auditory and reward responses to concert hall stimuli. Before the fMRI testing, 18 participants rated their preferences to a solo-instrumental passage and an orchestral motif simulated in eight room acoustic conditions outside an MRI scanner to identify their most liked and disliked conditions. In the MRI, the most-liked (reverberation time, RT = 1.0-2.8 s) and most-disliked (RT = 7.2 s) conditions, along with the [anechoic and scrambled versions] anechoic and scrambled versions of the musical passages were presented. The auditory cortex was found to be sensitive to the temporal coherence of the stimuli as it exhibited stronger activations for simpler stimuli, i.e., the solo-instrumental and anechoic conditions, than for stimuli containing temporally incoherent auditory objects-the orchestral and reverberant conditions. In contrasts between liked and disliked reverberant stimuli, a reward response in the basal ganglia was detected in a region of interest analysis using a temporal derivative model of the hemodynamic response function. This response may indicate differences in preference between subtle variations in room acoustics applied to the same musical passage.

Effects of test method and participant musical training on preference ratings of stimuli with different reverberation times.

Selecting an appropriate listening test design for concert hall research depends on several factors, including listening test method and participant critical-listening experience. Although expert listeners afford more reliable data, their perceptions may not be broadly representative. The present paper contains two studies that examined the validity and reliability of the data obtained from two listening test methods, a successive and a comparative method, and two types of participants, musicians and non-musicians. Participants rated their overall preference of auralizations generated from eight concert hall conditions with a range of reverberation times (0.0-7.2 s). Study 1, with 34 participants, assessed the two methods. The comparative method yielded similar results and reliability as the successive method. Additionally, the comparative method was rated as less difficult and more preferable. For study 2, an additional 37 participants rated the stimuli using the comparative method only. An analysis of variance of the responses from both studies revealed that musicians are better than non-musicians at discerning their preferences across stimuli. This result was confirmed with a k-means clustering analysis on the entire dataset that revealed five preference groups. Four groups exhibited clear preferences to the stimuli, while the fifth group, predominantly comprising non-musicians, demonstrated no clear preference.