For Release: September 26, 2017

Best Paper Awards Announced for Upcoming AES New York Convention

— Honors presented for Best Peer-Reviewed Papers and Best Student Papers —

The 143rd Audio Engineering Society Convention, taking place October 18 to 21 at the Jacob Javits Center in Manhattan, will feature the presentation of the annual AES “Best Peer-Reviewed Paper Award” and “Best Student Paper Award” distinctions, which honor outstanding achievement in academic papers being presented at the convention. The awards will be presented during the Opening Ceremonies on October 18 by AES New York Convention Papers Co-chairs Braxton Boren and Areti Andreopoulou.

This year’s “Best Peer-Reviewed Paper Award” distinction will go to Sean Olive, Todd Welti, and Omid Khonsaripour, each from HARMAN International – Northridge, CA, USA, for their paper “A Statistical Model that Predicts Listeners’ Preference Ratings of In-Ear Headphones: Part 1 — Listening Test Results and Acoustic Measurements.” The paper will be presented on Thursday, October 19, as part of Paper Session P07. ("Part 2 – Development and Validation of the Model" will be presented as part of Paper Session P14 on Friday, October 20).

The “Best Student Paper Award” goes to Sarah R. Smith and Mark F. Bocko, both students of University of Rochester – Rochester, NY, USA, for their paper “Modeling the Effect of Rooms on Frequency Modulated Tones,” which will also be presented on Friday, October 20, as part of Paper Session P15. 

Abstract for Best Peer Reviewed Paper – “A Statistical Model that Predicts Listeners’ Preference Ratings of In-Ear Headphones: Part 1—Listening Test Results and Acoustic Measurements”
Part 1 of this paper presented the results of controlled listening tests where 71 listeners both trained and untrained gave preference ratings for 30 different models of in-ear (IE) headphones. Both trained and untrained listeners preferred the headphone equalized to Harman IE target curve. Objective measurements indicated the magnitude response of the headphone appeared to be a predictor of its preference rating, and the further it deviated from the response of the Harman IE target curve the less it was generally preferred. Part 2 presents a linear regression model that accurately predicts the headphone preference ratings (r = 0.91) based on the size, standard deviation and slope of the magnitude response deviation from the response of the Harman IE headphone target curve.

Abstract for Best Student Paper Award – “Modeling the Effects of Rooms on Frequency Modulated Tones”
This paper describes how reverberation impacts the instantaneous frequency tracks of modulated audio signals. Although this effect has been observed in a number of contexts, less work has been done relating these deviations to acoustical parameters of the reverberation. This paper details the instantaneous frequency deviations resulting from a sum of echoes or a set of resonant modes and emphasizes the conditions that maximize the resulting effect. Results of these models are compared with the observed instantaneous frequencies of musical vibrato tones filtered with the corresponding impulse responses. It is demonstrated that reduced models may adequately reproduce the deviations when the signal is filtered by only the early or low frequency portion of a recorded impulse response.

Best Paper Awards and other presentations are all part of this year’s AES New York Convention, taking place next month. The convention will be co-located with the independent and adjacent NAB Show New York 2017. Registration, at any level, for AES New York 2017 will give attendees access to the NAB Show New York exhibition floor and the content in the NAB Show New York’s Core Package (a $75 value). Register now, upgrade to the All Access registration for the Maximum Audio experience, including all of the research papers and engineering briefs within the hundreds of sessions that make up the full Technical Program, and reserve housing for the 143rd AES Convention at aesshow.com. Online advance registration discounts end soon.