I am trying to implement an SLM app for iOS using AudioKit. Therefore I need to determine different loudness values to a) display the current loudness (averaged over a second) and b) do further calculations (e.g. to calculate the "Equivalent Continuous Sound Level" over a longer time span). The app should be able to track frequency-weighted decibel values like dB(A) and dB(C).
I do understand that some of the issues im facing are related to my general lack of understanding in the field of signal and audio processing. My question is how one would approach this task with AudioKit. I will describe my current process and would like to get some input:
Create an instance of AKMicrophone and a AKFrequencyTracker on this microphone
Create a Timer instance with some interval (currently 1/48_000.0)
Inside the timer: retrieve the amplitude and frequency. Calculate a decibel value from the amplitude with 20 * log10(amplitude) + calibrationOffset (calibration offset will be determined per device model with the help of a professional SLM). Calculate offsets for the retrieved frequency according to frequency-weighting (A and C) and apply these to the initial dB value. Store dB, dB(A) and dB(C) values in an array.
Calculate the average for arrays over the give timeframe (1 second).
I read somewhere else that using a Timer this is not the best approach. What else is there that I could use for the "sampling"? What exactly is the frequency of AKFrequencyTracker? Will this frequency be sufficient to determine dB(A) and dB(C) values or will I need an AKFFTTap for this? How are values retrieved from the AKFrequencyTracker averaged, i.e. what time frame is used for the RMS?
Possibly related questions: Get dB(a) level from AudioKit in swift, AudioKit FFT conversion to dB?
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I am looking for a way to code or find a program that can record the chirps of crickets either live or through a prerecorded audio file (large ~24 hours) for a lab experiment.
I'm not too sure how to approach this as I'm a web developer, but I have experience with JS and python, along with libraries. My initial idea was to use Matplotlib to produce an audio visualizer, and then count each time a certain range of db is reached which matches the db of a cricket chirp, but I have no idea how to approach it.
I have successfully visualized the chirps on a online spectrum analyzer (Spectrum Visualizer of Audio Chirps), and can see it clearly, however I don't know how I can use code to count each "chirp" and record it along with the date and time for each chirp in a table of values / dataset of some sort.
Any guidance or help would be greatly appreciated!
Really naive solution: For every unit of time (column of pixels in the spectrogram), you can calculate the sum of all the values in a column. For example, if all the pixels in a column are black, the sum for that column will be 0, if some of them are colored, the sum will be >0.
Then loop over the sums: if at a certain step you go from 0 to > 0, and then after a while you go back to 0, you've hit a peak.
If the output is too "noisy", you can use a small threshold value instead of 0. Tweak it until results seem OK. This works well when the input background noise is pretty much the same all the way through, but if it's skewed up and down during the whole recording, you need something more complicated (for example, the threshold constantly changes with the average of the last n sums)
Or you can Google "peak detection algorithm" and implement one of them. Or you can Google "peak detection library" in your favourite language and use one of them.
I want to create similar sound to theremin using touch coordinate on screen. I'm using y axis as frequency, x axis as amplitude.
Due to my small research I believe I can create it using AKOscillator or AKFMOscillator from AudioKit framework (please let me know if any other oscillator works better in this case). I'm open to other frameworks like built-in AudioToolbox (MIDINoteMessage etc.) if I can create similar sound to theremin.
Here it says theremin has two oscillators. One with fixed-frequency on 260kHz and one is dynamic between 257-260kHz. It superimposes their output (it takes difference of them I guess?). And it outputs between frequency between 0-3 kHz.
When I create sounds using AKFMOscillator with baseFrequency between 257-260 kHz, it sounds high-pitched.
When I try with one oscillator range between 0-3kHz it sounds very robotic. How I can simulate timbre of theremin?
How can I make it sound better? Should I mix two oscillators? I tried mixing with AKMixer but when both oscillators use same frequency and amplitude, it makes no difference.
I tried to mapping to nearest note (auto-tune), I tried limiting the frequency between 3-4 octaves. It sounds better but still not good as theremin.
What should use ( AKOscillator or AKFMOscillator, OscillatorBank), with which parameters (rampDuration, baseFrequency, modulationIndex, amplitude) to simulate more thereminish sound?
Update:
I did some more research and played with Synth One presets. Now, I know I need two oscillators mixed (both set to saw-shape wave). Changing ADSR(envelope) values to specific ranges creates richer sound (this gives the instrumental sound type). And a lfo to create the wavy (or spooky) sound effect. Playing notes (specific frequencies) creates good sounds, if you play every frequency in between note frequencies it doesn't sound good.
I'm trying to demodulate a signal using GNU Radio Companion. The signal is FSK (Frequency-shift keying), with mark and space frequencies at 1200 and 2200 Hz, respectively.
The data in the signal text data generated by a device called GeoStamp Audio. The device generates audio of GPS data fed into it in real time, and it can also decode that audio. I have the decoded text version of the audio for reference.
I have set up a flow graph in GNU Radio (see below), and it runs without error, but with all the variations I've tried, I still can't get the data.
The output of the flow graph should be binary (1s and 0s) that I can later convert to normal text, right?
Is it correct to feed in a wav audio file the way I am?
How can I recover the data from the demodulated signal -- am I missing something in my flow graph?
This is a FFT plot of the wav audio file before demodulation:
This is the result of the scope sink after demodulation (maybe looks promising?):
UPDATE (August 2, 2016): I'm still working on this problem (occasionally), and unfortunately still cannot retrieve the data. The result is a promising-looking string of 1's and 0's, but nothing intelligible.
If anyone has suggestions for figuring out the settings on the Polyphase Clock Sync or Clock Recovery MM blocks, or the gain on the Quad Demod block, I would greatly appreciate it.
Here is one version of an updated flow graph based on Marcus's answer (also trying other versions with polyphase clock recovery):
However, I'm still unable to recover data that makes any sense. The result is a long string of 1's and 0's, but not the right ones. I've tried tweaking nearly all the settings in all the blocks. I thought maybe the clock recovery was off, but I've tried a wide range of values with no improvement.
So, at first sight, my approach here would look something like:
What happens here is that we take the input, shift it in frequency domain so that mark and space are at +-500 Hz, and then use quadrature demod.
"Logically", we can then just make a "sign decision". I'll share the configuration of the Xlating FIR here:
Notice that the signal is first shifted so that the center frequency (middle between 2200 and 1200 Hz) ends up at 0Hz, and then filtered by a low pass (gain = 1.0, Stopband starts at 1 kHz, Passband ends at 1 kHz - 400 Hz = 600 Hz). At this point, the actual bandwidth that's still present in the signal is much lower than the sample rate, so you might also just downsample without losses (set decimation to something higher, e.g. 16), but for the sake of analysis, we won't do that.
The time sink should now show better values. Have a look at the edges; they are probably not extremely steep. For clock sync I'd hence recommend to just go and try the polyphase clock recovery instead of Müller & Mueller; chosing about any "somewhat round" pulse shape could work.
For fun and giggles, I clicked together a quick demo demod (GRC here):
which shows:
Can any one please explain clearly why the time of a signal is an independent variable while the amplitude is a dependent one? I referred to some results from google but i coul not figure it out.
the raw signal what ever it is measuring it is a function of time "time-domain" which means if we plotted the "time-domain" we will get one axes for the time (t), which is independent, and another axes for the Amplitude (x(t)) which is dependent variable on the time.
Note that: the independent variable "time" could be continous or discrete. Continuos means the time could be represented as intervals eg: t=(0 -> 800). while the discrete time signal could be represented as a countable set, eg: t = (1/2,5/2,/8/2).
Also, if you have a signal with the independent variable represents the TIME, then this signal is multidimensional "more than one dimention"
Strange question. Definitely more philosophical than programming-related. Here's my view.
One explanation is that a signal is a (mathematical) function of time. That means that for each time you have one and only one amplitude value. In contrast, the same amplitude value could be found at several (or none) time instants. So if you considered amplitude as independent variable and time as dependent of amplitude, the relationship wouldn't be a function. It's easier to ask something whose answer is known to be unique (amplitude obtained at a given time) than it is to ask something that might have none, one, or arbirarily many answers (time instants corresponding to a given ampitude level).
Also, psychologically we are more often interested in finding out "what the signal value is at a given instant", as opposed to knowing "at which instants a given signal value is found". For example, questions of the type "what will the weather be like tomorrow?" are more common than "on which days from now on will the weather be sunny?". So the point of view of time as independent and amplitude as dependent on time seems more natural.
The time is a universal independent variable because nothing can change the time. On multiple time instance there can be the same value of amplitude. But on two amplitudes there can not be one time. Independent variables are those which can not be changed with respect to other parameter.
This question already has answers here:
What kind of logarithm functions / methods are available in objective-c / cocoa-touch?
(3 answers)
Closed 9 years ago.
I am building a game using Sprite Kit and I want to gradually increase the difficulty (starting at 1.0) based on the time since starting the game.
Someone suggested that I should use a logarithmic calculation for this but I'm unsure how to implement this in Objective-C.
- (float)difficulty
{
timeSinceStart = ???; // I don't what kind of object this should be to make it play nice w/ `log`
return log(???);
}
Update #1
I know that I need to use the log method but I'm uncertain what values I need to pass to it.
Objective C is a superset of the C language, therefore you can use "math.h".
The function that computes the natural logarithm from "math.h" is double log(double x);
EDIT
Since you want the difficulty to increase as a function of time, you would pass the time as the argument to log(double x). How you would use that to calculate and change the "difficulty" is an entirely different question.
If you want to change the shape of the curve, either multiply the expression by a constant, as in 2*log(x) or multiply the parameter by a constant, as in log(2*x). You will have to look at the individual curves to see what will work best for your specific application.
Since log(1.0) == 0 you probably want to do some scaling and translation. Use something like 1.0 + log(1.0 + c * time). At time zero this will give a difficulty of 1.0, and as time advances the difficulty will increase at a progressively slower pace whose rate is determined by c. Small values such as c = 0.01 will give a slow ramp-up, larger values will ramp-up faster.
#pjs gave a pretty clear answer. As to how to figure out the time: You probably want the amount of time spent actually playing, rather than elapsed time since launching the game.
So you will nee to track total time played, game after game.
I suggest you create an entry in NSUserDefaults. You can save and load double values to user defaults using the NSUserDefaults methods setDouble:forKey: and doubleForKey:
I would create an instance variable startPlayingTime, type double
When you start the game action running, capture the start time using
startPlayingTime = [NSDate timeIntervalSinceReferenceDate];
When the user passes the game/exits to the background, use
NSTimeInterval currentPlayTime = [NSDate timeIntervalSinceReferenceDate] - startPlayingTime;
Then read the total time played from user defaults, add currentPlayTime to it, and save it back to user defaults.
You can then make your game difficulty based on
difficulty = log(1+ c * totalPlayTime);
(as explained by pjs, above) and pick some appropriate value for C.