The cavity tone……

In September 2017, I attended the 20th International Conference on Digital Audio Effects in Edinburgh. At this conference, I presented my work on a real-time physically derived model of a cavity tone. The cavity tone is one of the fundamental aeroacoustic sounds, similar to previously described Aeolian tone. The cavity tone commonly occurs in aircraft when opening bomb bay doors or by the cavities left when the landing gear is extended. Another example of the cavity tone can be seen when swinging a sword with a grooved profile.

The physics of operation is a can be a little complicated. To try and keep it simple, air flows over the cavity and comes into contact with air at a different velocity within the cavity. The movement of air at one speed over air at another cause what’s known as shear layer between the two. The shear layer is unstable and flaps against the trailing edge of the cavity causing a pressure pulse. The pressure pulse travels back upstream to the leading edge and re-enforces the instability. This causes a feedback loop which will occur at set frequencies. Away from the cavity the pressure pulse will be heard as an acoustic tone – the cavity tone!

A diagram of this is shown below:

Like the previously described Aeolian tone, there are equations to derive the frequency of the cavity tone. This is based on the length of the cavity and the airspeed. There are a number of modes of operation, usually ranging from 1 – 4. The acoustic intensity has also been defined which is based on airspeed, position of the listener and geometry of the cavity.

The implementation of an individual mode cavity tone is shown in the figure below. The Reynolds number is a dimensionless measure of the ratio between the inertia and viscous force in the flow and Q relates to the bandwidth of the passband of the bandpass filter.

Comparing our model’s average frequency prediction to published results we found it was 0.3% lower than theoretical frequencies, 2.0% lower than computed frequencies and 6.4% lower than measured frequencies. A copy of the pure data synthesis model can be downloaded here.

 

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The final whistle blows

Previously, we discussed screams, applause, bouncing and pouring water. Continuing our examination of every day sounds, we bring you… the whistle.

This one is a little challenging though. To name just a few, there are pea whistles, tin whistles, steam whistles, dog whistles and of course, human whistling. Covering all of this is a lot more than a single blog entry. So lets stick to the standard pea whistle or pellet whistle (or ‘escargot’ or barrel whistle because of its snail-like shape), which is the basis for a lot of the whistles that you’ve heard.

metal pea whistle

 

Typical metal pea whistle, featuring mouthpiece,  bevelled edge and sound hole where air can escape, and barrel-shaped air chamber and a pellet inside.

 

Whistles are the oldest known type of flute. They have a stopped lower end and a flue that directs the player’s breath from the mouth hole at the upper end against the edge of a hole cut in the whistle wall, causing the enclosed air to vibrate. Most whistle instruments have no finger holes and sound only one pitch.

A whistle produces sound from a stream of gas, most commonly air, and typically powered by steam or by someone blowing air. The conversion of energy to sound comes from an interaction between the air stream and a solid material.

In a pea whistle, the air stream enters through the mouthpiece. It hits the bevel (sloped edge for the opening) and splits, outwards into the air and inwards filling the air chamber. It continues to swirl around and fill the chamber until the air pressure inside  is so great that it pops out of the sound hole (a small opening next to the bevel), making room for the process to start over again. The dominant pitch of the whistle is determined by the rate at which air packs and unpacks the air chamber. The movement of air forces the pea or pellet inside the chamber to move around and around. This sometimes interrupts the flow of air and creates a warble to the whistle sound.

The size of the whistle cavity determines the volume of air contained in the whistle and the pitch of the sound produced. The air fills and empties from the chamber so many times per second, which gives the fundamental frequency of the sound.

The whistle construction and the design of the mouthpiece also have a dramatic effect on sound. A whistle made from a thick metal will produce a brighter sound compared to the more resonant mellow sound if thinner metal is used. Modern whistles are produce using different types of plastic, which increases the tones and sounds now available. The design of the mouthpiece can also dramatically alter the sound. Even a few thousandths of an inch difference in the airway, angle of the blade, size or width of the entry hole, can make a drastic difference as far as volume, tone, and chiff (breathiness or solidness of the sound) are concerned. And according to the whistle Wiki page, which might be changed by the time you read this, ‘One characteristic of a whistle is that it creates a pure, or nearly pure, tone.’

Well, is all of that correct? When we looked at the sounds of pouring hot and cold water we found that the simple explanations were not correct. In explaining the whistle, can we go a bit further than a bit of handwaving about the pea causing a warble? Do the different whistles differ a lot in sound?

Lets start with some whistle sounds. Here’s a great video where you get to hear a dozen referee’s whistles.

Looking at the spectrogram below, you can see that all the whistles produce dominant frequencies somewhere between 2200 and 4400 Hz. Some other features are also apparent. There seems to be some second and even third harmonic content. And it doesn’t seem to be just one frequency and its overtones. Rather, there are two or three closely spaced frequencies whenever the whistle is blown.

Referee Whistles

But this sound sample is all fairly short whistle blows, which could be why the pitches are not constant. And one should never rely on just one sample or one audio file (as the authors did here). So lets look at just one long whistle sound.

joe whistle spec

joe whistle

You can see that it remains fairly constant, and the harmonics are clearly present, though I can’t say if they are partly due to dynamic range compression or any other processing. However, there are semi-periodic dips or disruptions in the fundamental pitch. You can see this more clearly in the waveform, and this is almost certainly due to the pea temporarily blocking the sound hole and weakening the sound.

The same general behaviour appears with other whistles, though with some variation in the dips and their rate of occurrence, and in the frequencies and their strengths.

Once I started writing this blog, I was pointed to the fact that Perry Cook had already discussed synthesizing whistle sounds in his wonderful book Real Sound Synthesis for Interactive Applications. In building up part of a model of a police/referee whistle, he wrote

 ‘Experiments and spectrograms using real police/referee whistles showed that when the pea is in the immediate region of the jet oscillator, there is a decrease in pitch (about 7%), an increase in amplitude (about 6 dB), and a small increase in the noise component (about 2 dB)… The oscillator exhibits three significant harmonics: f, 2f and 3f at 0 dB, -10 dB and -25 dB, respectively…’

With the exception of the increase in amplitude due to the pea (was that a typo?), my results are all in rough agreement with his. So depending on whether I’m a glass half empty / glass half full kind of person, I could either be disappointed that I’m just repeating what he did, or glad that my results are independently confirmed.

This information from a few whistle recordings should be good enough to characterise the behaviour and come up with a simple, controllable synthesis. Jiawei Liu took a different approach. In his Master’s thesis, he simulated whistles using computational fluid dynamics and acoustic finite element simulation. It was very interesting work, as was a related approach by Shia, but they’re both a bit like using a sledgehammer to kill a fly. Massive effort and lots of computation, when a model that probably sounds just as good could have been derived using semi-empirical equations that model aeroacoustic sounds directly, as discussed in our previous blog entries on sound synthesis of an Aeolian Harp, a Propeller. Sword sounds, swinging objects or Aeolian tones.

There’s been some research into automatic identification of referee whistle sounds, for instance, initial work of Shirley and Oldfield in 2011 and then a more advanced algorithm a few years later. But these are either standard machine learning techniques, or based on the most basic aspects of the whistle sound, like its fundamental frequency. In either case, they don’t use much understanding of the nature of the sound. But I suppose that’s fine. They work, they enable intelligent production techniques for sports broadcasts,  and they don’t need to delve into the physical or perceptual aspects.

I said I’d stick to pellet whistles, but I can’t resist mentioning a truly fascinating and unusual synthesis of another whistle sound. Steam locomotives were equipped with train whistles for warning and signalling. to generate the sound, the train driver pulls a cord in the driver’s cabin, thereby opening a valve, so that steam shoots out of an gap and against the sharp edge of a bell. This makes the bell vibrate rapidly, which creates a whistling sound. In 1972, Herbert Chaudiere created an incredibly detailed sound system for model trains. This analogue electronic system  generated all the memorable sounds of the steam locomotive; the bark of exhausting steam, the rhythmic toll of the bell, and the wail of the chime whistle, and reproduced these sounds from a loudspeaker carried in the model locomotive.

The preparation of this blog entry also illustrates some of the problems with crowd sourced metadata and user generated tagging. When trying to find some good sound examples, I searched the whole’s most popular sound effects archive, freesound, for ‘pea whistle’. It came up with only one hit, a recording of steam and liquid escaping from a pot of boiling black-eyed peas!

References:

  • Chaudiere, H. T. (1972). Model Railroad Sound system. Journal of the Audio Engineering Society, 20(8), 650-655.
  • Liu, J. (2012). Simulation of whistle noise using computational fluid dynamics and acoustic finite element simulation, MSc Thesis, U. Kentucky.
  • Shia, Y., Da Silvab, A., & Scavonea (2014), G. Numerical Simulation of Whistles Using Lattice Boltzmann Methods, ISMA, Le Mans, France
  • Cook, P. R. (2002). Real sound synthesis for interactive applications. CRC Press.
  • Oldfield, R. G., & Shirley, B. G. (2011, May). Automatic mixing and tracking of on-pitch football action for television broadcasts. In Audio Engineering Society Convention 130
  • Oldfield, R., Shirley, B., & Satongar, D. (2015, October). Application of object-based audio for automated mixing of live football broadcast. In Audio Engineering Society Convention 139.

Applied Science Journal Article

We are delighted to announce the publication of our article titled, Sound Synthesis of Objects Swinging through Air Using Physical Models in the Applied Science Special Issue on Sound and Music Computing.

 

The Journal is a revised and extended version of our paper which won a best paper award at the 14th Sound and Music Computing Conference which was held in Espoo, Finland in July 2017. The initial paper presented a physically derived synthesis model used to replicate the sound of sword swings using equations obtained from fluid dynamics, which we discussed in a previous blog entry. In the article we extend listening tests to include sound effects of metal swords, wooden swords, golf clubs, baseball bats and broom handles as well as adding in a cavity tone synthesis model to replicate grooves in the sword profiles. Further test were carried out to see if participants could identify which object our model was replicating by swinging a Wii Controller.
The properties exposed by the sound effects model could be automatically adjusted by a physics engine giving a wide corpus of sounds from one simple model, all based on fundamental fluid dynamics principles. An example of the sword sound linked to the Unity game engine is shown in this video.
 

 

Abstract:
A real-time physically-derived sound synthesis model is presented that replicates the sounds generated as an object swings through the air. Equations obtained from fluid dynamics are used to determine the sounds generated while exposing practical parameters for a user or game engine to vary. Listening tests reveal that for the majority of objects modelled, participants rated the sounds from our model as plausible as actual recordings. The sword sound effect performed worse than others, and it is speculated that one cause may be linked to the difference between expectations of a sound and the actual sound for a given object.
The Applied Science journal is open access and a copy of our article can be downloaded here.

Bounce, bounce, bounce . . .

bounce

Another in our continuing exploration of everyday sounds (Screams, Applause, Pouring water) is the bouncing ball. It’s a nice one for a blog entry since there are only a small number of papers focused on bouncing, which means we can give a good overview of the field. It’s also one of those sounds that we can identify very clearly; we all know it when we hear it. It has two components that can be treated separately; the sound of a single bounce and the timing between bounces.

Let’s consider the second aspect. If we drop a ball from a certain height and ignore any drag, the time it takes to hit the ground is completely determined by gravity. When it hits the ground, some energy is absorbed on impact. And so it may be traveling downwards with a velocity v1 just before impact, and after impact travels upwards with velocity v2. The ratio v2/v1 is called the coefficient of restitution (COR). A high COR means that the ball travels back up almost to its original height, and a low COR means that most energy is absorbed and it only travels up a short distance.

Knowing COR, one can use simple equations of motion to determine the time between each bounce. And since the sum of the times between bounces is a convergent series, one can find the maximum time until it stops bouncing. Conversely, measuring the coefficient of friction from times between bounces is literally a tabletop physics experiment (Aguiar 2003, Farkas 2006, Schwarz 2013). And kinetic energy depends on the square of the velocity, so we know how much energy is lost with each bounce, which also gives an idea of how the sound levels of successive bounces should decrease.

[The derivation of all this has been left to the reader 😊. But again, its straightforward application of the equations of motion that give time dependence of position and velocity under constant acceleration]

Its not that hard to extend this approach, for instance by including air drag or sloped surfaces. But if you put the ball on a vibrating platform, all sorts of wonderful nonlinear behaviour can be observed; chaos, locking and chattering (Luck 1993).

For instance, have a look at the following video; which shows some interesting behaviour where bouncing balls all seem to organise onto one side of a partition.

So much for the timing of bounces, but what about the sound of a single bounce? Well, Nagurka (2004) modelled the bounce as a mass-spring-damper system, giving the time of contact for each bounce. It provides a little more realism by capturing some aspects of the bounce sound, Stoelinga (2007) did a detailed analysis of bouncing and rolling sounds. It has a wealth of useful information, and deep insights into both the physics and perception of bouncing, but stops short of describing how to synthesize a bounce.

To really capture the sound of a bounce, something like modal synthesis should be used. That is, one should identify the modes that are excited for impact of a given ball on a given surface, and their decay rates. Farnell measured these modes for some materials, and used those values to synthesize bounces in Designing Sound . But perhaps the most detailed analysis and generation of such sounds, at least as far as I’m aware, is in the work of Davide Rocchesso and his colleagues, leaders in the field of sound synthesis and sound design. They have produced a wealth of useful work in the area, but an excellent starting point is The Sounding Object.

Are you aware of any other interesting research about the sound of bouncing? Let us know.

Next week, I’ll continue talking about bouncing sounds with discussion of ‘the audiovisual bounce-inducing effect.’

References

  • Aguiar CE, Laudares F. Listening to the coefficient of restitution and the gravitational acceleration of a bouncing ball. American Journal of Physics. 2003 May;71(5):499-501.
  • Farkas N, Ramsier RD. Measurement of coefficient of restitution made easy. Physics education. 2006 Jan;41(1):73.
  • Luck, J.M. and Mehta, A., 1993. Bouncing ball with a finite restitution: chattering, locking, and chaos. Physical Review E, 48(5), p.3988.
  • Nagurka, M., Shuguang H,. “A mass-spring-damper model of a bouncing ball.” American Control Conference, 2004. Vol. 1. IEEE, 2004.
  • Schwarz O, Vogt P, Kuhn J. Acoustic measurements of bouncing balls and the determination of gravitational acceleration. The Physics Teacher. 2013 May;51(5):312-3.
  • Stoelinga C, Chaigne A. Time-domain modeling and simulation of rolling objects. Acta Acustica united with Acustica. 2007 Mar 1;93(2):290-304.

Exciting research at the upcoming Audio Engineering Society Convention

aes143

About five months ago, we previewed the last European Audio Engineering Society Convention, which we followed with a wrap-up discussion. The next AES  convention is just around the corner, October 18 to 21st in New York. As before, the Audio Engineering research team here aim to be quite active at the convention.

These conventions are quite big, with thousands of attendees, but not so large that you get lost or overwhelmed. Away from the main exhibition hall is the Technical Program, which includes plenty of tutorials and presentations on cutting edge research.

So here, we’ve gathered together some information about a lot of the events that we will be involved in, attending, or we just thought were worth mentioning. And I’ve gotta say, the Technical Program looks amazing.

Wednesday

One of the first events of the Convention is the Diversity Town Hall, which introduces the AES Diversity and Inclusion Committee. I’m a firm supporter of this, and wrote a recent blog entry about female pioneers in audio engineering. The AES aims to be fully inclusive, open and encouraging to all, but that’s not yet fully reflected in its activities and membership. So expect to see some exciting initiatives in this area coming soon.

In the 10:45 to 12:15 poster session, Steve Fenton will present Alternative Weighting Filters for Multi-Track Program Loudness Measurement. We’ve published a couple of papers (Loudness Measurement of Multitrack Audio Content Using Modifications of ITU-R BS.1770, and Partial loudness in multitrack mixing) showing that well-known loudness measures don’t correlate very well with perception when used on individual tracks within a multitrack mix, so it would be interesting to see what Steve and his co-author Hyunkook Lee found out. Perhaps all this research will lead to better loudness models and measures.

At 2 pm, Cleopatra Pike will present a discussion and analysis of Direct and Indirect Listening Test Methods. I’m often sceptical when someone draws strong conclusions from indirect methods like measuring EEGs and reaction times, so I’m curious what this study found and what recommendations they propose.

The 2:15 to 3:45 poster session will feature the work with probably the coolest name, Influence of Audience Noises on the Classical Music Perception on the Example of Anti-cough Candies Unwrapping Noise. And yes, it looks like a rigorous study, using an anechoic chamber to record the sounds of sweets being unwrapped, and the signal analysis is coupled with a survey to identify the most distracting sounds. It reminds me of the DFA faders paper from the last convention.

At 4:30, researchers from Fraunhofer and the Technical University of Ilmenau present Training on the Acoustical Identification of the Listening Position in a Virtual Environment. In a recent paper in the Journal of the AES, we found that training resulted in a huge difference between participant results in a discrimination task, yet listening tests often employ untrained listeners. This suggests that maybe we can hear a lot more than what studies suggest, we just don’t know how to listen and what to listen for.

Thursday

If you were to spend only one day this year immersing yourself in frontier audio engineering research, this is the day to do it.

At 9 am, researchers from Harman will present part 1 of A Statistical Model that Predicts Listeners’ Preference Ratings of In-Ear Headphones. This was a massive study involving 30 headphone models and 71 listeners under carefully controlled conditions. Part 2, on Friday, focuses on development and validation of the model based on the listening tests. I’m looking forward to both, but puzzled as to why they weren’t put back-to-back in the schedule.

At 10 am, researchers from the Tokyo University of the Arts will present Frequency Bands Distribution for Virtual Source Widening in Binaural Synthesis, a technique which seems closely related to work we presented previously on Cross-adaptive Dynamic Spectral Panning.

From 10:45 to 12:15, our own Brecht De Man will be chairing and speaking in a Workshop on ‘New Developments in Listening Test Design.’ He’s quite a leader in this field, and has developed some great software that makes the set up, running and analysis of listening tests much simpler and still rigorous.

In the 11-12:30 poster session, Nick Jillings will present Automatic Masking Reduction in Balance Mixes Using Evolutionary Computing, which deals with a challenging problem in music production, and builds on the large amount of research we’ve done on Automatic Mixing.

At 11:45, researchers from McGill will present work on Simultaneous Audio Capture at Multiple Sample Rates and Formats. This helps address one of the challenges in perceptual evaluation of high resolution audio (and see the open access journal paper on this), ensuring that the same audio is used for different versions of the stimuli, with only variation in formats.

At 1:30, renowned audio researcher John Vanderkooy will present research on how a  loudspeaker can be used as the sensor for a high-performance infrasound microphone. In the same session at 2:30, researchers from Plextek will show how consumer headphones can be augmented to automatically perform hearing assessments. Should we expect a new audiometry product from them soon?

At 2 pm, our own Marco Martinez Ramirez will present Analysis and Prediction of the Audio Feature Space when Mixing Raw Recordings into Individual Stems, which applies machine learning to challenging music production problems. Immediately following this, Stephen Roessner discusses a Tempo Analysis of Billboard #1 Songs from 1955–2015, which builds partly on other work analysing hit songs to observe trends in music and production tastes.

At 3:45, there is a short talk on Evolving the Audio Equalizer. Audio equalization is a topic on which we’ve done quite a lot of research (see our review article, and a blog entry on the history of EQ). I’m not sure where the novelty is in the author’s approach though, since dynamic EQ has been around for a while, and there are plenty of harmonic processing tools.

At 4:15, there’s a presentation on Designing Sound and Creating Soundscapes for Still Images, an interesting and unusual bit of sound design.

Friday

Judging from the abstract, the short Tutorial on the Audibility of Loudspeaker Distortion at Bass Frequencies at 5:30 looks like it will be an excellent and easy to understand review, covering practice and theory, perception and metrics. In 15 minutes, I suppose it can only give a taster of what’s in the paper.

There’s a great session on perception from 1:30 to 4. At 2, perceptual evaluation expert Nick Zacharov gives a Comparison of Hedonic and Quality Rating Scales for Perceptual Evaluation. I think people often have a favorite evaluation method without knowing if its the best one for the test. We briefly looked at pairwise versus multistimuli tests in previous work, but it looks like Nick’s work is far more focused on comparing methodologies.

Immediately after that, researchers from the University of Surrey present Perceptual Evaluation of Source Separation for Remixing Music. Techniques for remixing audio via source separation is a hot topic, with lots of applications whenever the original unmixed sources are unavailable. This work will get to the heart of which approaches sound best.

The last talk in the session, at 3:30 is on The Bandwidth of Human Perception and its Implications for Pro Audio. Judging from the abstract, this is a big picture, almost philosophical discussion about what and how we hear, but with some definitive conclusions and proposals that could be useful for psychoacoustics researchers.

Saturday

Grateful Dead fans will want to check out Bridging Fan Communities and Facilitating Access to Music Archives through Semantic Audio Applications in the 9 to 10:30 poster session, which is all about an application providing wonderful new experiences for interacting with the huge archives of live Grateful Dead performances.

At 11 o’clock, Alessia Milo, a researcher in our team with a background in architecture, will discuss Soundwalk Exploration with a Textile Sonic Map. We discussed her work in a recent blog entry on Aural Fabric.

In the 2 to 3:30 poster session, I really hope there will be a live demonstration accompanying the paper on Acoustic Levitation.

At 3 o’clock, Gopal Mathur will present an Active Acoustic Meta Material Loudspeaker System. Metamaterials are receiving a lot of deserved attention, and such advances in materials are expected to lead to innovative and superior headphones and loudspeakers in the near future.

 

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), Brecht De Man, Marco Martinez and Alessia Milo from the Audio Engineering research team within the Centre for Digital Music  will all be there.
 

 

Physically Derived Sound Synthesis Model of a Propeller

I recently presented my work on the real-time sound synthesis of a propeller at the 12th International Audio Mostly Conference in London. This sound effect is a continuation of my research into aeroacoustic sounds generated by physical models; an extension of my previous work on the Aeolian harp, sword sounds and Aeolian tones.

A demo video of the propeller model attached to an aircraft object in unity is given here. I use the Unity Doppler effect which I have since discovered is not the best and adds a high-pitched artefact but you’ll get the idea! The propeller physical model was implemented in Pure Data and transferred to Unity using the Heavy compiler.

So, when I was looking for an indication of the different sound sources in a propeller sound I found an excellent paper by JE Marte and DW Kurtz. (A review of aerodynamic noise from propellers, rotors, and lift fans. Jet Propulsion Laboratory, California Institute of Technology, 1970) This paper provides a breakdown of the different sound sources, replicated for you here.

The sounds are split into periodic and broadband groups. In the periodic sounds, there are rotational sounds associated with the forces on the blade and interaction and distortion effects. The first rotational sound is the Loading sounds. These are associated with the thrust and torque of each propeller blade.

To picture these forces, imagine you are sitting on an aircraft wing, looking down the span, travelling at a fixed speed and uniform air flowing over the aerofoil. From your point of view the wing will have a lift force associated with it and a drag force. Now if we change the aircraft wing to a propeller blade with similar profile to an aerofoil, spinning at a set RPM. If you are sitting at a point on the blade the thrust and torque will be constant at the point you are sat.

Now stepping off the propeller blade and examining the disk of rotation the thrust and torque forces will appear as pulses at the blade passing frequency. For example, a propeller with 2 blades, rotating at 2400 RPM will have a blade passing frequency of 80Hz. A similar propeller with 4 blades, rotating at the same RPM will have a blade passing frequency of 160Hz.

Thickness noise is the sound generated as the blade moves the air aside when passing. This sound is found to be small when blades are moving at the speed of sound, 343 m/s, (known as a speed of Mach 1), and is not considered in our model.

Interaction and distortion effects are associated with helicopter rotors and lift fans. Because these have horizontally rotating blades an effect called blade slap occurs, where the rotating blade passes through the vortices shed by the previous blade causing a large slapping sound. Horizontal blades also have AM and FM modulated signals related with them as well as other effects. Since we are looking at propellers that spin mostly vertically, we have omitted these effects.

The broadband sounds of the propeller are closely related to the Aeolian tone models I have spoken about previously. The vortex sounds are from the vortex shedding, identical to out sword model. This difference in this case is that a propeller has a set shape which more like an aerofoil than a cylinder.

In the Aeolian tone paper, published at AES, LA, 2016, it was found that for a cylinder the frequency can be determined by an equation defined by Strouhal. The ratio of the diameter, frequency and airspeed are related by the Strouhal number, found for a cylinder to be approximately 0.2. In the paper D Brown and JB Ollerhead, Propeller noise at low tip speeds. Technical report, DTIC Document, 1971, a Strouhal number of 0.85 was found for propellers. This was used in our model, along with the chord length of the propeller instead of the diameter.

We also include the wake sound in the Aeolian tone model which is similar to the turbulence sounds. These are only noticeable at high speeds.

The paper by Martz et. al. outlines a procedure by Hamilton Standard, a propeller manufacturer, for predicting the far field loading sounds. Along with the RPM, number of blades, distance, azimuth angle we need the blade diameter, and engine power. We first decided which aircraft we were going to model. This was determined by the fact that we wanted to carry out a perceptual test and had a limited number of clips of known aircraft.

We settled on a Hercules C130, Boeing B17 Flying Fortress, Tiger Moth, Yak-52, Cessna 340 and a P51 Mustang. The internet was searched for details like blade size, blade profile (to calculate chord lengths along the span of the blade), engine power, top speed and maximum RPM. This gave enough information for the models to be created in pure data and the sound effect to be as realistic as possible.

This enables us to calculate the loading sounds and broadband vortex sounds, adding in a Doppler effect for realism. What was missing is an engine sound – the aeroacoustic sounds will not happen in isolation in our model. To rectify this a model from Andy Farnell’s Designing Sound was modified to act as our engine sound.

A copy of the pure data software can be downloaded from this site, https://code.soundsoftware.ac.uk/hg/propeller-model. We performed listening tests on all the models, comparing them with an alternative synthesis model (SMS) and the real recordings we had. The tests highlighted that the real sounds are still the most plausible but our model performed as well as the alternative synthesis method. This is a great result considering the alternative method starts with a real recording of a propeller, analyses it and re-synthesizes it. Our model starts with real world physical parameters like the blade profile, engine power, distance and azimuth angles to produce the sound effect.

An example of the propeller sound effect is mixed into this famous scene from North by Northwest. As you can hear the effect still has some way to go to be as good as the original but this physical model is the first step in incorporating fluid dynamics of a propeller into the synthesis process.

From the editor: Check out all Rod’s videos at https://www.youtube.com/channel/UCIB4yxyZcndt06quMulIpsQ

A copy the paper published at Audio Mostly 2017 can be found here >> Propeller_AuthorsVersion

12th International Audio Mostly Conference, London 2017

by Rod Selfridge & David Moffat. Photos by Beici Liang.

Audio Mostly – Augmented and Participatory Sound and Music Experiences, was held at Queen Mary University of London between 23 – 26 August. The conference brought together a wide variety of audio and music designers, technologists, practitioners and enthusiasts from all over the world.

The opening day of the conference ran in parallel with the Web Audio Conference, also being held at Queen Mary, with sessions open to all delegates. The day opened with a joint Keynote from the computer scientist and author of the highly influential sound effect book – Designing Sound, Andy Farnell. Andy covered a number of topics and invited audience participation which grew into a discussion regarding intellectual property – the pros and cons if it was done away with.

Andy Farnell

The paper session then opened with an interesting talk by Luca Turchet from Queen Mary’s Centre for Digital Music. Luca presented his paper on The Hyper Mandolin, an augmented music instrument allowing real-time control of digital effects and sound generators. The session concluded with the second talk I’ve seen in as many months by Charles Martin. This time Charles presented Deep Models for Ensemble Touch-Screen Improvisation where an artificial neural network model has been used to implement a live performance and sniffed touch gestures of three virtual players.

In the afternoon, I got to present my paper, co-authored by David Moffat and Josh Reiss, on a Physically Derived Sound Synthesis Model of a Propeller. Here I continue the theme of my PhD by applying equations obtained through fluid dynamics research to generate authentic sound synthesis models.

Rod Selfridge

The final session of the day saw Geraint Wiggins, our former Head of School at EECS, Queen Mary, present Callum Goddard’s work on designing Computationally Creative Musical Performance Systems, looking at questions like what makes performance virtuosic and how this can be implemented using the Creative Systems Framework.

The oral sessions continued throughout Thursday, one presentation that I found interesting was by Anna Xambo titles Turn-Taking and Chatting in Collaborative Music Live Coding. In this research the authors explored collaborative music live coding using the live coding environment and pedagogical tool EarSketch, focusing on the benefits to both performance and education.

Thursday’s Keynote was by Goldsmith’s Rebecca Fiebrink, who was mentioned in a previous blog, discussing how machine learning can be used to support human creative experiences, aiding human designers for rapid prototyping and refinement of new interactions within sound and media.

Rebecca Fiebrink

The Gala Dinner and Boat Cruise was held on Thursday evening where all the delegates were taken on a boat up and down the Thames, seeing the sites and enjoying food and drink. Prizes were awarded and appreciation expressed to the excellent volunteers, technical teams, committee members and chairpersons who brought together the event.

Tower Bridge

A session on Sports Augmentation and Health / Safety Monitoring was held on Friday Morning which included a number of excellent talks. The presentation of the conference went to Tim Ryan who presented his paper on 2K-Reality: An Acoustic Sports Entertainment Augmentation for Pickup Basketball Play Spaces. Tim re-contextualises sounds appropriated from a National Basketball Association (NBA) video game to create interactive sonic experiences for players and spectators. I was lucky enough to have a play around with this system during a coffee break and can easily see how it could give an amazing experience for basketball enthusiasts, young and old, as well as drawing in a crowd to share.

Workshops ran on Friday afternoon. I went to Andy Farnell’s Zero to Hero Pure Data Workshop where participants managed to go from scratch to having a working bass drum, snare and high-hat synthesis models. Andy managed to illustrate how quickly these could be developed and included in a simple sequencer to give a basic drum machine.

Throughout the conference a number of fixed media, demos were available for delegates to view as well as poster sessions where authors presented their work.

Alessia Milo

Live music events were held on both Wednesday and Friday. A joint session titled Web Audio Mostly Concert was held on Wednesday which was a joint event for delegates of Audio Mostly and the Web Audio Conference. This included an augmented reality musical performance, a human-playable robotic zither, the Hyper Mandolin and DJs.

The Audio Mostly Concert on the Friday included a Transmusicking performance from a laptop orchestra from around the world, where 14 different performers collaborated online. The performance was curated by Anna Xambo. Alan Chamberlain and David De Roure performed The Gift of the Algorithm, which was a computer music performance inspired by Ada Lovelace. The wood and the water was an immersive performance of interactivity and gestural control of both a Harp and lighting for the performance, by Balandino Di Donato and Eleanor Turner. GrainField, by Benjamin Matuszewski and Norbert Schnell, was an interactive audio performance that demanded entire audience involvement, for the performance to exist, this collective improvisational piece demonstrated a how digital technology can really be used to augment the traditional musical experience. GrainField was awarded the prize for the best musical performance.

Adib Mehrabi

The final day of the conference was a full day’s workshop. I attended the one titled Designing Sounds in the Cloud. The morning was spent presenting two ongoing European Horizon 2020 projects, Audio Commons (www.audiocommons.org/) and Rapid-Mix. The Audio Commons initiative aims to promote the use of open audio content by providing a digital ecosystem that connects content providers and creative end users. The Rapid-Mix project focuses on multimodal and procedural interactions leveraging on rich sensing capabilities, machine learning and embodied ways to interact with sound.

Before lunch we took part in a sound walk around the Queen Mary Mile End Campus, with one of each group blindfolded, informing the other what they could hear. The afternoon session had teams of participants designing and prototyping new ways to use the APIs from each of the two Horizon 2020 projects – very much in the feel of a hackathon. We devised a system which captured expressive Italian hand gestures using the Leap Motion and classified them using machine learning techniques. Then in pure data each new classification triggered a sound effect taken from the Freesound website (part of the audio commons project). If time would have allowed the project would have been extended to have pure data link to the audio commons API and play sound effects straight from the web.

Overall, I found the conference informative, yet informal, enjoyable and inclusive. The social events were spectacular and ones that will be remembered by delegates for a long time.