Echolocation projects typically rely on inexpensive distance sensors and the human brain to do most of the processing. The team creating SNAP: Augmented Echolocation are using much stronger computational power to translate robotic vision into a 3D soundscape.
The SNAP team starts with an Intel RealSense R200. The first part of the processing happens here because it outputs a depth map which takes the heavy lifting out of robotic vision. From here, an AAEON Up board, packaged with the RealSense, takes the depth map and associates sound with the objects in the field of view.
Binaural sound generation is a feat in itself and works on the principle that our brains process incoming sound from both ears to understand where a sound originates. Our eyes do the same thing. We are bilateral creatures so using two ears or two eyes to understand our environment is already part of the human operating system.
In the video after the break, we see a demonstration where the wearer doesn’t need to move his head to realize what is happening in front of him. Instead of a single distance reading, where the wearer must systematically scan the area, the wearer simply has to be pointed the right way.
Life is good if you are a couch potato music enthusiast. Bluetooth audio allows the playing of all your music from your smartphone, and apps to control your hi-fi give you complete control over your listening experience.
Not quite so for [Daniel Landau] though. His Cambridge Audio amplifier isn’t quite the latest generation, and he didn’t possess a handy way to turn it on and off without resorting to its infrared remote control. It has a proprietary interface of some kind, but nothing wireless to which he could talk from his mobile device.
His solution is fairly straightforward, which in itself says something about the technology available to us in the hardware world these days. He took a Raspberry Pi with the Home Assistant home automation package and the LIRC infrared subsystem installed, and had it drive an infrared LED within range of the amplifier’s receiver. Coupled with the Home Assistant app, he was then able to turn the amplifier on and off as desired. It’s a fairly simple use of the software in question, but this is the type of project upon which so much more can later be built.
Have a beautiful antique radio that’s beyond repair? This ESP8266 based Internet radio by [Edzelf] would be an excellent starting point to get it running again, as an alternative to a Raspberry-Pi based design. The basic premise is straightforward: an ESP8266 handles the connection to an Internet radio station of your choice, and a VS1053 codec module decodes the stream to produce an audio signal (which will require some form of amplification afterwards).
Besides the excellent documentation (PDF warning), where this firmware really shines is the sheer number of features that have been added. It includes a web interface that allows you to select an arbitrary station as well as cycle through presets, adjust volume, bass, and treble.
If you prefer physical controls, it supports buttons and dials. If you’re in the mood for something more Internet of Things, it can be controlled by the MQTT protocol as well. It even supports a color TFT screen by default, although this reduces the number of pins that can be used for button input.
The firmware also supports playing arbitrary .mp3 files hosted on a server. Given the low parts count and the wealth of options for controlling the device, we could see this device making its way into doorbells, practical jokes, and small museum exhibits.
There are few greater follies in the world of electronics than that of an electronic engineering student who has just discovered the world of hi-fi audio. I was once that electronic engineering student and here follows a tale of one of my follies. One that incidentally taught me a lot about my craft, and I am thankful to say at least did not cost me much money.
It must have been some time in the winter of 1991/92, and being immersed in student radio and sound-and-light I was party to an intense hi-fi arms race among the similarly afflicted. Some of my friends had rich parents or jobs on the side and could thus afford shiny amplifiers and the like, but I had neither of those and an elderly Mini to support. My only option therefore was to get creative and build my own. And since the ultimate object of audio desire a quarter century ago was a valve (tube) amp, that was what I decided to tackle.
Nowadays, building a valve amp is a surprisingly straightforward process, as there are many online suppliers who will sell you a kit of parts from the other side of the world. Transformer manufacturers produce readily available products for your HT supply and your audio output matching, so to a certain extent your choice of amp is simply a case of picking your preferred circuit and assembling it. Back then however the world of electronics had extricated itself from the world of valves a couple of decades earlier, so getting your hands on the components was something of a challenge. I cut out the power supply by using a scrap Dymar Electronics instrument enclosure which had built-in HT and heater rails ready to go, but the choice of transformers and high-voltage capacitors was something of a challenge.
Pulling the amplifier out of storage in 2017, I’m going in blind. I remember roughly what I did, but the details have been obscured by decades of other concerns. So in an odd meeting with my barely-adult self, it’s time to take a look at what I made. Where did I get it right, and just how badly did I get it wrong?
[Roland]’s workflow consists of breaking up a recording from his backyard into one second clips, loading them in to a Python program and running some machine learning code to determine whether the clip is a recording of a bat or not and using this to determine the number of bats flying around. He uses several Python libraries to do this including Tensorflow and LibROSA.
The Python code breaks each one second clip into twenty-two parts. For each part, he determines the max, min, mean, standard deviation, and max-min of the sample – if multiple parts of the signal have certain features (such as a high standard deviation), then the software has detected a bat call. Armed with this, [Roland] turned his head to the machine learning so that he could offload the work of detecting the bats. Again, he turned to Python and the Keras library.
Once you fall deep enough into the rabbit hole of any project, specific information starts getting harder and harder to find. At some point, trusting experts becomes necessary, even if that information is hard to find, obtuse, or incomplete. [turingbirds] was having this problem with Bessel filters, namely that all of the information about them was scattered around the web and in textbooks. For anyone else who is having trouble with these particular filters, or simply wants to learn more about them, [turingbirds] has put together a guide with all of the information he has about them.
For those who don’t design audio circuits full-time, a Bessel filter is a linear, passive bandpass filter that preserves waveshapes of signals that are within the range of the filter’s pass bands, rather than distorting them in some way. [turingbirds]’s guide goes into the foundations of where the filter coefficients come from, instead of blindly using lookup tables like he had been doing.
For anyone else who uses these filters often, this design guide looks to be a helpful tool. Of course, if you’re new to the world of electronic filters there’s no reason to be afraid of them. You can even get started with everyone’s favorite: an Arduino.
[Alex Lynham] has been creating digital guitar pedals for a while and after releasing the Atom Smasher, a glitchy lo-fi digital delay pedal, he had people start asking him how he designed digital effects pedals rather than analog effects. In fact, he had enough interest, that he wrote an article on it.
The article starts with some background on [Alex], the pedals he’s built and why he chose not to work on pedals full-time. Eventually, the article gets to the how [Alex] designed the Atom Smasher. He starts by describing the chip he used, the same one that many hobbyists, as well as commercial builders, use for delay based effects – the SpinSemi FV-1.
The FV-1 is a SMD chip used for digital delays and other effects that require a delay line – reverbs, choruses, flangers, etc. It’s programmed with an assembly-style language called SpinASM. [Alex] goes over some of the tools and references he used when designing for the pedal. He also has a list of tips for would-be effect pedal designers which work whether you’re designing digital or analogue effects.