We previewed the 142nd, 143rd, 144th and 145th Audio Engineering Society (AES) Conventions, which we also followed with wrap-up discussions. Then we took a break, but now we’re back to preview the 147th AES convention, October 16 to 19 in New York. As before, the Audio Engineering research team here aim to be quite active at the convention.
We’ve gathered together some information about a lot of the research-oriented events that caught our eye as being unusual, exceptionally high quality, involved in, attending, or just worth mentioning. And this Convention will certainly live up to the hype.
Wednesday October 16th
When I first read the title of the paper ‘Evaluation of Multichannel Audio in Automobiles versus Mobile Phones‘, presented at 10:30, I thought it was a comparison of multichannel automotive audio versus the tinny, quiet mono or barely stereo from a phone. But its actually comparing results of a listening test for stereo vs multichannel in a car, with results of a listening test for stereo vs multichannel for the same audio, but from a phone and rendered over headphones. And the results look quite interesting.
Deep neural networks are all the rage. We’ve been using DNNs to profile a wide variety of audio effects. Scott Hawley will be presenting some impressive related work at 9:30, ‘Profiling Audio Compressors with Deep Neural Networks.’
We previously presented work on digital filters that closely match their analog equivalents. We pointed out that such filters can have cut-off frequencies beyond Nyquist, but did not explore that aspect. ‘Digital Parametric Filters Beyond Nyquist Frequency‘, at 10 am, investigates this idea in depth.
I like a bit of high quality mathematical theory, and that’s what you get in Tamara Smyth’s 11:30 paper ‘On the Similarity between Feedback/Loopback Amplitude and Frequency Modulation‘, which shows a rather surprising (at least at first glance) equivalence between two types of feedback modulation.
There’s an interesting paper at 2pm, ‘What’s Old Is New Again: Using a Physical Scale Model Echo Chamber as a Real-Time Reverberator‘, where reverb is simulated not with impulse response recordings, or classic algorithms, but using scaled models of echo chambers.
At 4 o’clock, ‘A Comparison of Test Methodologies to Personalize Headphone Sound Quality‘ promises to offer great insights not just for headphones, but into subjective evaluation of audio in general.
There’s so many deep learning papers, but the 3-4:30 poster ‘Modal Representations for Audio Deep Learning‘ stands out from the pack. Deep learning for audio most often works with raw spectrogram data. But this work proposes learning modal filterbank coefficients directly, and they find it gives strong results for classification and generative tasks. Also in that session, ‘Analysis of the Sound Emitted by Honey Bees in a Beehive‘ promises to be an interesting and unusual piece of work. We talked about their preliminary results in a previous entry, but now they’ve used some rigorous audio analysis to make deep and meaningful conclusions about bee behaviour.
Immerse yourself in the world of virtual and augmented reality audio technology today, with some amazing workshops, like Music Production in VR and AR, Interactive AR Audio Using Spark, Music Production in Immersive Formats, ISSP: Immersive Sound System Panning, and Real-time Mixing and Monitoring Best Practices for Virtual, Mixed, and Augmented Reality. See the Calendar for full details.
Thursday, October 17th
‘An Automated Approach to the Application of Reverberation‘, at 9:30, is the first of several papers from our team, and essentially does something to algorithmic reverb similar to what “Parameter Automation in a Dynamic Range Compressor” did for a dynamic range compressor.
Why do public address (PA) systems sound for large venues sound so terrible? They actually have regulations for speech intelligibility. But this is only measured in empty stadiums. At 11 am, ‘The Effects of Spectators on the Speech Intelligibility Performance of Sound Systems in Stadia and Other Large Venues‘ looks at the real world challenges when the venue is occupied.
Two highlights of the 9-10:30 poster session, ‘Analyzing Loudness Aspects of 4.2 Million Musical Albums in Search of an Optimal Loudness Target for Music Streaming‘ is interesting, not just for the results, applications and research questions, but also for the fact that involved 4.2 million albums. Wow! And there’s a lot more to audio engineering research than what one might think. How about using acoustic sensors to enhance autonomous driving systems, which is a core application of ‘Audio Data Augmentation for Road Objects Classification‘.
Audio forensics is a fascinating world, where audio engineering is often applied to unusually but crucially. One such situation is explored at 2:15 in ‘Forensic Comparison of Simultaneous Recordings of Gunshots at a Crime Scene‘, which involves looking at several high profile, real world examples.
Friday, October 18th
There are two papers looking at new interfaces for virtual reality and immersive audio mixing, ‘Physical Controllers vs. Hand-and-Gesture Tracking: Control Scheme Evaluation for VR Audio Mixing‘ at 10:30, and ‘Exploratory Research into the Suitability of Various 3D Input Devices for an Immersive Mixing Task‘ at 3:15.
At 9:15, J. T. Colonel from our group looks into the features that relate, or don’t relate, to preference for multitrack mixes in ‘Exploring Preference for Multitrack Mixes Using Statistical Analysis of MIR and Textual Features‘, with some interesting results that invalidate some previous research. But don’t let negative results discourage ambitious approaches to intelligent mixing systems, like Dave Moffat’s (also from here) ‘Machine Learning Multitrack Gain Mixing of Drums‘, which follows at 9:30.
Continuing this theme of mixing analysis and automation is the poster ‘A Case Study of Cultural Influences on Mixing Preference—Targeting Japanese Acoustic Major Students‘, shown from 3:30-5, which does a bit of meta-analysis by merging their data with that of other studies.
Just below, I mention the need for multitrack audio data sets. Closely related, and also much needed, is this work on ‘A Dataset of High-Quality Object-Based Productions‘, also in the 3:30-5 poster session.
Saturday, October 19th
We’re approaching a world where almost every surface can be a visual display. Imagine if every surface could be a loudspeaker too. Such is the potential of metamaterials, discussed in ‘Acoustic Metamaterial in Loudspeaker Systems Design‘ at 10:45.
Another session, 9 to 11:30 has lots of interesting presentations about music production best practices. At 9, Amandine Pras presents ‘Production Processes of Pop Music Arrangers in Bamako, Mali‘. I doubt there will be many people at the convention who’ve thought about how production is done there, but I’m sure there will be lots of fascinating insights. This is followed at 9:30 by ‘Towards a Pedagogy of Multitrack Audio Resources for Sound Recording Education‘. We’ve published a few papers on multitrack audio collections, sorely needed for researchers and educators, so its good to see more advances.
I always appreciate filling the gaps in my knowledge. And though I know a lot about sound enhancement, I’ve never dived into how its done and how effective it is in soundbars, now widely used in home entertainment. So I’m looking forward to the poster ‘A Qualitative Investigation of Soundbar Theory‘, shown 10:30-12. From the title and abstract though, this feels like it might work better as an oral presentation. Also in that session, the poster ‘Sound Design and Reproduction Techniques for Co-Located Narrative VR Experiences‘ deserves special mention, since it won the Convention’s Best Peer-Reviewed Paper Award, and promises to be an important contribution to the growing field of immersive audio.
Its wonderful to see research make it into ‘product’, and ‘Casualty Accessible and Enhanced (A&E) Audio: Trialling Object-Based Accessible TV Audio‘, presented at 3:45, is a great example. Here, new technology to enhance broadcast audio for those with hearing loss iwas trialed for a popular BBC drama, Casualty. This is of extra interest to me since one of the researchers here, Angeliki Mourgela, does related research, also in collaboration with BBC. And one of my neighbours is an actress who appears on that TV show.
I encourage the project students working with me to aim for publishable research. Jorge Zuniga’s ‘Realistic Procedural Sound Synthesis of Bird Song Using Particle Swarm Optimization‘, presented at 2:30, is a stellar example. He created a machine learning system that uses bird sound recordings to find settings for a procedural audio model. Its a great improvement over other methods, and opens up a whole field of machine learning applied to sound synthesis.
At 3 o’clock in the same session is another paper from our team, Angeliki Mourgela presenting ‘Perceptually Motivated Hearing Loss Simulation for Audio Mixing Reference‘. Roughly 1 in 6 people suffer from some form of hearing loss, yet amazingly, sound engineers don’t know what the content will sound like to them. Wouldn’t it be great if the engineer could quickly audition any content as it would sound to hearing impaired listeners? That’s the aim of this research.
About three years ago, I published a meta-analysis on perception of high resolution audio, which received considerable attention. But almost all prior studies dealt with music content, and there are good reasons to consider more controlled stimuli too (noise, tones, etc). The poster ‘Discrimination of High-Resolution Audio without Music‘ does just that. Similarly, perceptual aspects of dynamic range compression is an oft debated topic, for which we have performed listening tests, and this is rigorously investigated in ‘Just Noticeable Difference for Dynamic Range Compression via “Limiting” of a Stereophonic Mix‘. Both posters are in the 3-4:30 session.
The full program can be explored on the Convention Calendar or the Convention website. Come say hi to us if you’re there! Josh Reiss (author of this blog entry), J. T. Colonel, Angeliki Mourgela and Dave Moffat from the Audio Engineering research team within the Centre for Digital Music, will all be there.
Intelligent sound engineering 