I am currently creating an application which signals readiness to other devices using a high frequency sound.
(transmitter): A device will produce a short burst of sound of around 20khz.
(receiver): Another device will be listening for a sound at this frequency at a small distance from the transmitter(10m approx) The device recieves audio data from a microphone
The background noise will be fairly loud, varying from around 0 - 10khz(about human speech range), and would be produced by a small crowd of people.
I need the receiving device to be able to detect the 20khz sound, separated from the noise,
and know the time at which it was received.
Any help with an appropriate algorithm, a library, or even better, code in C or
Objc to detect this high frequency sound would be greatly appreciated.
20 kHz may be pushing it, as (a) most sound cards have low pass (anti aliassing) filters at 18 - 20 kHz and (b) most speakers and microphones tend to have a poor response at 20 kHz. You might want to consider say 15 kHz ?
The actual detection part should be easy - just implement a narrow band pass filter at the tone frequency, rectify the output and low pass filter (e.g. 10 Hz).
You may want to look into FFT (Fast Fourier Transform). This algorithm will allow you to analyse a waveform and convert it to the frequency spectrum for further analysis.
If this is for Mac OS or iOS, I'd start looking into Core Audio's Audio Units.
1 Here's Apple's Core Audio Overview.
2 Some AudioUnits for Mac OS
3 Or for iOS AudioUnit Hosting
A sound with that high frequency will not travel at all with the iphone speaker.
Related
Is the bit rate of black screen shown when video is muted same as the original video's bit rate or is it significantly less because it is just a black screen?
It is significantly less. Since there is essentially no video information being sent to the remote party. How much depends on a lot of factors (connection quality etc).
I just did a quick test and the outgoing bit rate at 640x480 # 27fps was around 900 kbps to 1 mbps. Disabling the video track of the stream resulted in an outgoing bitrate of 30 kbps.
Please keep in mind that this was only a simple test I did. You can get this kind of information yourself by evaluating the reports in peerConnection.getStats
Some documentation and libraries for getStats
https://www.w3.org/TR/webrtc-stats
https://github.com/muaz-khan/getStats
https://www.callstats.io/2015/07/06/basics-webrtc-getstats-api/
Came across chrome://webrtc-internals, which has inbuilt tracking for bit rates and has other good features.
As seen in graph, bit rate before video was muted was ~150k which reduces to ~30k on muting the video.
I'm trying to generate high quality voice-over using Microsoft Speech API. What kind of values I should pass in to this constructor to guarantee high quality audio?
The .wav file will be used latter to feed FFmpeg, so audio will be re-encoded latter to a more compact form. My main goal is keep the voice as clear as I can, but I really don't know which values guarantee the best quality perceived by humans.
First of all, just to let you know I haven't used this Speech API, I'll give you an answer based on my Audio processing work.....
You can choose EncodingFormat.Pcm for Pulse Code Modulation
samplesPerSecond is sampling frequency. Because it is voice you can cover it with 16000hz for sure. If you are really perfectionist you can go with 22050 for example. Higher the value is, the audio file size will be larger. If file size isn't a problem you can even go with 32000 or 44100 but there won't be much noticable difference....
bitsPerSample - go with 16 if possible
1 or 2, mono or stereo ..... it won't affect the quality of the sound
averageBytesPerSecond ..... this would be samplesPerSecond*bytesPerSample (for example 22050*2)
blockAlign ..... this would be Bytes Per Sample*numberOfChanels (for example if you have 16bit PCM Mono audio, 16bits are 2 bytes, Mono is 1, so blockAlign is 2*1)
That last one, the byte array doesn't speaks much for itself, I'm not sure what it serves for, I believe the first 6 arguments are enough for audio to be generated.
I hope this was helpful
Cheers
The wife asked for a device to make the xmas lights 'rock' with the best of music. I am going to use an Arduino micro-controller to control relays hooked up to the lights, sending down 6 signals from C# winforms to turn them off and on. I want to use NAduio to separate the amplitude and rhythm to send the six signals. For a specific range of hertz like an equalizer with six bars for the six signals, then the timing from the rhythm. I have seen the WPF demo, and the waveform seems like the answer. I want to know how to get those values real time while the song is playing.
I'm thinking ...
1. Create a simple mp3 player and load all my songs.
2. Start the songs playing.
3. Sample the current dynamics of the song and put that into an integer that I can send to which channel on the Arduino micro-controller via usb.
I'm not sure how to capture real time the current sound information and give integer values for that moment. I can read the e.MaxSampleValues[0] values real time while the song is playing, but I want to be able to distinguish what frequency range is active at that moment.
Any help or direction would be appreciated for this interesting project.
Thank you
Sounds like a fun signal processing project.
Using the NAudio.Wave.WasapiLoopbackCapture object you can get the audio data being produced from the sound card on the local computer. This lets you skip the 'create an MP3 player' step, although at the cost of a slight delay between sound and lights. To get better synchronization you can do the MP3 decoding and pre-calculate the beat patterns and output states during playback. This will let you adjust the delay between sending the outputs and playing the audio block those outputs were generated from, getting near perfect synchronization between lights and music.
Once you have the samples, the next step is to use an FFT to find the frequency components. Fortunately NAudio includes a class to help with this: NAudio.Dsp.FastFourierTransform. (Thank you Mark!) Take the output of the FFT() function and sum out the frequency ranges you want for each controlled light.
The next step is Beat Detection. There's an interesting article on this here. The main difference is that instead of doing energy detection on a stream of sample blocks you'll be using the data from your spectral analysis stage to feed the beat detection algorithm. Those ranges you summed become inputs into individual beat detection processors, giving you one output for each frequency range you defined. You might want to add individual scaling/threshold factors for each frequency group, with some sort of on-screen controls to adjust these for best effect.
At the end of the process you will have a stream of sample blocks, each with a set of output flags. Push the flags out to your Arduino and queue the samples to play, with a delay on either of those operations to achieve your synchronization.
I just bought Digital heart beat rate sensor:
http://www.dealextreme.com/p/digital-heart-beat-rate-sensor-3-5mm-data-port-16009
And I'm looking how I can make application for iOS to work with.
Sensor has 3.5mm jack and I can detect signal with audio framework on iOS.
Can you give me some guidelines how to start with detecting these signals into heart beat rates?
That sensor looks rather like one I have here in my junk box. If so, it generates a voltage signal which depends on the pressure exerted on it by the skin against which it is pressed. If there is a strong pulse at the point of pressure, I see a signal on an oscilloscope which has a component at the pulse rate: so it is at a frequency of around 1-2Hz.
This is WAY below the audio range, and in most audio interfaces would be filtered out before it ever got to the audio in ADC. I don't have a handy iPhone to check this on, but it would be bad design if the audio input did let such frequencies through. And Mr Jobs (R.I.P.) did not approve of bad design!
There is also a lot of interference at other frequencies: mains hum (50Hz here), and at lower frequencies spurious signals from muscle twitches.
To make this work, you would need some sort of signal conditioning. If it was up to me, I would use a high input impedance amplifier, with about a 0.1Hz - 10Hz passband, followed by a voltage to frequency converter. That would give me a tone, which i could set in the audio band, whose frequency varied up & down as the pressure on the sensor changes. That would let me use fairly simple frequency detection software to recover the pressure waveform, which could then be processed using autocorrelation or similar techniques to recover the heartbeat frequency. A DTMF decoder is not the right tool, though.
I did find when I played about with the senor that it was very touchy, responding to almost everything going, and it wouldn't be easy to pick out the heartbeat. Your sensor may be different, though.
i want to detect heart rate using iphone sdk does someone knows any method for calculating heartbeat rate?
Fast Fourier Transform is a class of algorithms that can quickly turn samples into an analysis that tells you how prominently ceratin frequencies occur in that sample. For more check out:
Wikipedia: FFT
Literate program example: Cooley-Tukey FFT
This is relevant to your problem because: (1) heart rate is itself a frequency, and (2) most of the sound that comes through the body that you can measure will be within a certain frequency range. Dropping frequencies outside this range means dropping all or mostly noise.
Good luck!
Well I've seen various implementations. Some of them use the accelerometer to detect minute movements in your arm/hand when you hold the phone, some of them can use the microphone, you could also do a manual 'tap' interface where you tap the screen while checking your own pulse.