Today QxLab’s Dr Abubakr Siddig presented collaborative work on immersive multimedia. As part of the ACM MMSys conference in University of Massachusetts Amherst Campus, the International Workshop on IMmersive Mixed and Virtual Environment Systems, MMVE 2019 is celebrating its 11th edition.
The paper, Fusion Confusion: Exploring Ambisonic Spatial Localisation for Audio-Visual Immersion Using the McGurk Effect, looked at the relationship between visual cues and spatial localisation for speech sounds.
The paper found that the McGurk Effect, where visual cues for sounds override what you hear, occurs for spatial audio but is not sensitive to whether the speech sound is aligned in space with the lips of the speaker.
The research, carried out by QxLab’s UCD based researchers and funded by two SFI centre’s CONNECT and INSIGHT.
Well done to AbuBakr, the presentation and demo were well received by the workshop attendees.
QxLab has two papers at the Irish Signals and Systems Conference in Maynooth University today. MSc student, Tong Mo presented work of speech Quality of Experience. Her research investigated how computer models for speech quality prediction in systems such as Skype or Google Hangouts. She developed an algorithm to minimise errors in the presence of jitter buffers.
A second paper was presented by PhD candidate Hamed Jahromi entitled, “Establishing Waiting Time Thresholds in Interactive Web Mapping Applications for Network QoE Management.” Hamed’s work looked at the perception of time in web applications. Is an additional delay of half a second noticeable if you have already waited 5 seconds for a Google Map page to load? Time is not absolute and Hamed wants to understand the impact of delays on web applications in order to optimise network resources for interactive applications other than speech and video streaming. This work was co-authored with Delcan T. Delaney from UCD Engineering and Brendan Rooney from UCD Psychology.
This research was sponsored by UCD School of Computer Science and the SFI CONNECT Centre for Future Networks.
Today is the UNESCO World Archives Day, highlighting the important work of archives and archivists in preserving our cultural heritage. The date was chosen to commemorate the creation of the International Council on Archives (ICA) founded on 9th of June 1948 under the auspices of the UNESCO. According to the ICA, “[a]rchives represent an unparalleled wealth. They are the documentary product of human activity and as such constitute irreplaceable testimonies of past events. They ensure the democratic functioning of societies, the identity of individuals and communities and the defense of human rights.”
Following quickly after the 6th June D-Day commemorations, today is a good day to highlight the important work that has been taking place to digitise and preserve the audio archives of the Nuremberg trials. Witnesses, lawyers and judges were recorded in their native tongues together with recordings of the live translations. This resulted in 775 hours of original trial audio recorded on 1,942 Presto gramophone discs and translations on Embossed tape, a clear-colored film also known as Amertape. While the tape degraded, the discs survived. The digitisation will be published next year but the fascinating story of was recently published by the Verge and PRI articles by Christopher Harland-Dunaway. University of Fribourg’s Ottar Johnsen worked with Stefano Cavaglieri, a colleague at the Swiss National Sound Archives and the International Court of Justices archivists using imaging and audio digital signal processing to capture the archive material. You can listen to it here:
Last week, at the 11th International Conference on Quality of Multimedia Experience (QoMEX), QxLab PhD student Alessandro Ragano presented our work on how audio archive stakeholders perceive quality in archive material. By examining the lifecycle from digitisation through restoration and consumption, the influence factors and stakeholders are highlighted. At QxLab we are interested in how audio digital signal processing techniques can be used in conjunction with data driven machine learning to capture, enhance and explore audio archives.
Alessandro’s research is supported in part by a research grant from Science Foundation Ireland (SFI) and is co-founded under the European Regional Development Fund under Grant No. 17/RC-PhD/3483. This publication has emanated from research supported by Insight which is supported by SFI under grant number 12/RC/2289. EB is supported by RAEng Research Fellowship RF/128 and a Turing Fellowship.