Every three months, we ask four Technical Committee (TC) chairs to select one article from the past nine months that they think is a representative of their TC’s published work over that time period. The newest round of Technical Area Picks have been selected, and will be free to read from June 1st to August 31st. Read on to find out which articles the chairs selected, along with a little insight from each chair about why they chose the article they did.

Architectural Acoustics
The acoustical characterization of clay pots in Ottoman architecture through experimental and numerical analysis,” by Gülnihan Atay, Zühre Sü Gül, and Onursal Önen.

TC Chair David S. Woolworth says, “Finding a representative paper for architectural acoustics over the last months is not realistic to due to the diversity of content; however, this paper combines numerous techniques used in AA to analyze an archeological acoustics question of acoustic intention.  I invite you to explore all of the AA papers over the last months and the diversity of topics from properties of surfaces to virtual environments.”

Architectural picks

Perception of noise from unmanned aircraft systems: Efficacy of metrics for indoor and outdoor listener positions,” by Nathan Green, Antonio J. Torija, and Carlos Ramos-Romero

TC Chair Alexandra Loubeau says, “This paper describes an investigation of annoyance to noise from a new class of small, unmanned aircraft. Results from the listening experiment were used to better understand the effect of listening environment and different aircraft operational modes, and sound quality metrics were used to identify factors that affect perception beyond the loudness level.”

Noise picks

Signal Processing
Remote passive acoustic signal detection using multi-scale correlation networks and network spectrum distance in marine environment,” by Hongwei Zhang, Haiyan Wang, Xuanming Liang, Yongsheng Yan, and Xiaohong Shen

TC Chair Geoffrey Edelmann says, “Massive amounts are being recorded in almost every aspect our lives. The data are complex and interconnected in such a way that does not lend themselves to standard tools. Graphs are a tool to model complex interactions among data. Graph signal processing (GSP) is the field of analyzing the products of classical tools such as Fourier transforms, filtering, and correlations in a highly structured methodology; as distances and interactions of data residing on graphs. Thus, different nodes (or signal types) reside as on different representational networks. This paper applies these high concepts to target detection, by comparing the spectra of two such networks. The GSP quantifies their similarity or dissimilarity of multi-scale correlation networks constructed from different time series data and tracking changes in nonlinear dynamics over time. Detection was shown even in low SNR regimes.”

Signal Processing picks

Speech Communication
Assessing accuracy of resonances obtained with reassigned spectrograms from the ‘ground truth’ of physical vocal tract models,” by Christine H. Shadle, Sean A. Fulop, Wei-Rong Chen, and D. H. Whalen.

TC Chair Benjamin Tucker says, “In the domain of speech communication spectrograms have been a crucial part of speech research. Recently, reassigned spectrograms have been shown to be an effective way to infer vocal tract resonances. Shadle et al. use three-dimensional printed physical tube models excited with white noise to validate the usefulness of reassigned spectrograms in identifying vocal tract resonances. The continual development of these methods could provide speech research with a solution to the long-standing challenge of identifying vocal tract resonances.”

Speech picks

Congratulations to all the authors whose work has been highlighted by the TC chairs!


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