AES Dublin 2019
Paper Session P08
P08 - Industry Issues
Thursday, March 21, 11:15 — 13:15 (Meeting Room 2)
Roisin Loughran, UCD - Dublin, Ireland
P08-1 Early Causes for Biodegradation of PVA/PVC Tapes for Audio Recording—Ana Paula da Costa, Instituto Superior Tecnico - Lisbon, Portugal; Teresa Rosa, Instituto Superior Tecnico - Lisbon, Portugal; Federica Bressan, Ghent University - Ghent, Belgium
The degradation of magnetic tapes is one of the main threats to the survival of our collective audio heritage. Archives around the world, big and small, are all concerned with the same challenge, that of counteracting the natural decay of plastic compounds. This study investigates the biodegradation of poly(vinyl alcohol)/poly(vinyl chloride) (PVA/PVC) blends tapes, namely audio magnetic tapes, using the spectrophotometry (FTIR), scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). The tapes (both sides) were studied in the light of their degradation in special conditions. The objective is to obtain more information regarding the polymer degradation of magnetic tapes for audio recording and how it affects the structural composition of the tapes. This study contributes to the long-term goal of building a structured knowledge base about diagnostic tools and recovery methods for magnetic tapes.
Convention Paper 10158 (Purchase now)
P08-2 Factors Contributing to Gender Imbalance in the Audio Industry—Shelley Ann McCarthy Buckingham, Limerick Institute of Technology - Limerick, Ireland; Malachy Ronan, Limerick Institute of Technology - Limerick, Ireland
This paper explores the factors contributing to gender imbalance in the audio industry. The two main goals were: (1) whether the traditional gender-related preference for “agency” or “communal” roles holds in the audio industry, and (2) uncover existing gender-based belief systems in the audio industry. The findings suggest that women in the audio industry possess more agentic personality traits than communal. In a surprising finding, men reported more communal personality traits than agentic. Women reported that they were unsuitable for technical and managerial roles making the need for more visible role models in these areas a critical concern.
Convention Paper 10159 (Purchase now)
P08-3 A Psychometric Evaluation of Emotional Responses to Horror Music—Duncan Williams, University of York - York, UK; Chia-Yu Wu, University of York - York, UK; Victoria Hodge, University of York - York, UK; Damian Murphy, University of York - York, UK; Peter Cowling, University of York - York, UK
This research explores and designs an effective experimental interface to evaluate people’s emotional responses to horror music. We studied methodological approaches by using traditional psychometric techniques to measure emotional responses, including self-reporting and galvanic skin response (GSR). GSR correlates with psychological arousal. It can help circumvent a problem in self-reporting where people are unwilling to report particular felt responses, or confuse perceived and felt responses. We also consider the influence of familiarity. Familiarity can induce learned emotional responses rather than listeners describing how it actually makes them feel. The research revealed different findings in self-reports and GSR data. Both measurements had an interaction between music and familiarity but show inconsistent results from the perspective of simple effects.
Convention Paper 10137 (Purchase now)
P08-4 Poster Introductions 5—N/A
The purpose of Poster Introductions at the end of certain paper sessions is to give the poster authors a chance to briefly outline what is in their paper and encourage people to come to their poster session and ask questions. • Audio Event Identification in Sports Media Content: the Case of Basketball—Panagiotis-Marios Filippidis; Nikolaos Vryzas; Rigas Kotsakis; Iordanis Thoidis; Charalampos Dimoulas; Charalampos Bratsas • Objective and Subjective Comparison of Several Machine Learning Techniques Applied for the Real-Time Emulation of the Guitar Amplifier Nonlinear Behavior—Thomas Schmitz; Jean-Jacques Embrechts • A Generalized Subspace Approach for Multichannel Speech Enhancement Using Machine Learning-Based Speech Presence Probability Estimation—Yuxuan Ke; Yi Hu; Chengshi Zheng; Xiaodong Li • Road Surface Wetness Detection Using Microphones and Convolutional Neural Networks—Giovani Pepe; Leonardo Gabrielli; Livio Ambrosini; Stefano Squartini; Luca Cattani • Primary Study on Removing Mains Hum from Recordings by Active Tone Cancellation Algorithms—Michal Luczynski