Here is a question for all you iPhone experts:
If you guys remember the sounds that modems used to make, or when one was trying to load a program from a cassette tape – I am trying to replicate this in an iPhone for a ham radio application. I have a stream of data (ASCII) and I need to encode it as AFSK at 1200 baud. So basically everything in the stream is converted to a series of 1200 and 2200 Hz tones. It needs to sound something like this: http://upload.wikimedia.org/wikipedia/commons/2/27/AFSK_1200_baud.ogg
I successfully built a bit array out of the string, but when I try to assign tones to each bit I get gaps in the sound, therefore it doesn’t demodulate correctly.
Any thought of how one should tackle this problem? Thank you.
The mobilesynth project is open-source. You might be able to scan that for code that generates the tones you need.
How are you assigning tones to the bits? Remember, a digital audio signal is just a stream of samples with values between -1 and 1. Perhaps there is a clipping issue between tone assignments. This can happen if the signal dives below -1 or above 1. If it stays above or below this range at a constant value, there will be no sound. Maybe you could output your stream of samples to check if this is the case. Or plug the output into an oscilloscope...
Also note that clicking can occur between "uneven" transitions of signals. For example if i output a sample with value 1 followed immediately by a sample with value -1, a click or pop will be produced.
Related
I've recently started working with audioworklets and am trying to figure out how to determine the pitch(s) from the input. I found a simple algorithm to use for a script processor, but the input values are different than a script processor and doesn't work. Plus each input array is only 128 units. So, how can I determine pitch using an audioworklet? As a bonus question, how do the values relate to the actual audio going in?
If it worked with a ScriptProcessorNode, it will work in an AudioWorklet, but you'll have to buffer the data in the worklet because, as you noted, you only get 128 frames per call. The ScriptProcessor gets anywhere from 256 to 16384.
The values going to the worklet are the actual values that are produced from the graph connected to the input. These are exactly the same values that would go to the script processor, except you get them in chunks of 128.
I want to compare 2 audio files programmatically.
For example: I have a sound file in my iPhone app, and then I record another one. I want to check if the existing sound matches the recorded sound or not ( - similar to voice recognition).
How can I accomplish this?
Have a server doing audio fingerprinting computation that is not suitable for mobile device anyway. And then your mobile app uploads your files to the server and gets the analysis result for display. So I don't think programming language implementing it matters much. Following are a few AF implementations.
Java: http://www.redcode.nl/blog/2010/06/creating-shazam-in-java/
VC++: http://code.google.com/p/musicip-libofa/
C#: https://web.archive.org/web/20190128062416/https://www.codeproject.com/Articles/206507/Duplicates-detector-via-audio-fingerprinting
I know the question has been asked a long time ago, but a clear answer could help someone else.
The libraries from Echoprint ( website: echoprint.me/start ) will help you solve the following problems :
De-duplicate a big collection
Identify (Track, Artist ...) a song on a hard drive or on a server
Run an Echoprint server with your data
Identify a song on an iOS device
PS: For more music-oriented features, you can check the list of APIs here.
If you want to implement Fingerprinting by yourself, you should read the docs listed as references here, and probably have a look at musicip-libofa on Google Code
Hope this will help ;)
Apply bandpass filter to reduce noise
Normalize for amplitude
Calculate the cross-correlation
It can be fairly Mhz intensive.
The DSP details are in the well known text:
Digital Signal Processing by
Alan V. Oppenheim and Ronald W. Schafer
I think as well you may try to select a few second sample from both audio track, mnormalise them in amplitude and reduce noise with a band pass filter and after try to use a correlator.
for instance you may take a 5 second sample of one of the thwo and made it slide over the second one computing a cross corelation for any time you shift. (be carefull that if you take a too small pachet you may have high correlation when not expeced and you will soffer the side effect due to the croping of the signal and the crosscorrelation).
After yo can collect an array with al the results of the cross correlation and get the index of the maximun.
You should then set experimentally up threshould o decide when yo assume the pachet to b the same. this will change depending on the quality of the audio track you are comparing.
I implemented a correator to receive and distinguish preamble in wireless communication. My script is actually done in matlab. if you are interested i can try to find the common part and send it to you.
It would be a too long code to be pasted hene in the forum. if you want just let me know and i will send it to ya asap.
cheers
I'm not sure if it's possible to achieve what I want, but basically I have a NSDictionary which represents a recording. It's a timeline of what sound id was played at what point in time.
I have it so that you can play back this timeline/recording, and it works perfectly.
I'm wondering if there is anyway to take this timeline, and export it as a single sound that could be saved to a computer if the device was synced with iTunes.
So basically I'm asking if I can take a timeline of sounds, play it back and have these sounds stitched together as a single sound, that can then be exported.
I'm using OpenAL as my sound framework and the sound files are all CAFs.
Any help or guidance is appreciated.
Thanks!
You will need:
A good understanding of linear PCM audio format (See Wikipedia's Linear PCM page).
A good understanding of audio sample-rates and some basic maths to convert your timings into sample-offsets.
An awareness of how two's-complement binary numbers (signed/unsigned, 16-bit, 32-bit, etc.) are stored in computers, and how the endian-ness of a processor affects this.
Patience, interest in learning, and a strong desire to get this working.
Here's what to do:
Enable file sharing in your app (UIFileSharingEnabled=YES in info.plist and write files to /Documents directory).
Render the used sounds into memory buffers containing linear PCM audio data (if they are not already, i.e. if they are compressed). You can do this using the offline rendering functionality of Audio Queues (see Apple audio queue docs). It will make things a lot easier if you render them all to the same PCM format and sample rate (For example 16-bit signed samples #44,100Hz, I'll use this format for all examples), and use the same format for your output. I recommend starting off with a Mono format then adding stereo once you get it working.
Choose an uncompressed output format and mix your sounds into a single stream:
3.1. Allocate a buffer large enough, or open a file stream to write to.
3.2. Write out any headers (for example if using WAV format output instead of raw PCM) and write zeros (or the mid-point of your sample range if not using a signed sample format) for any initial silence before your first sound starts. For example if you want 0.1 seconds silence before your first sound, write 4410 (0.1 * 44100) zero-samples i.e. write 4410 shorts (16-bit) all with zero.
3.3. Now keep track of all 'currently playing' sounds and mix them together. Start with an empty list of 'currently playing sounds and keep track of the 'current time' of the sample you are mixing, for each sample you write out increment the 'current time' by 1.0/sample_rate. When it gets time for another sound to start, add it to the 'currently playing' list with a sample offset of 0. Now to do the mixing, you iterate through all of the 'currently playing' sounds and add together their current sample, then increment the sample offset for each of them. Write the summed value into the output buffer. For example if soundA starts at 0.1 seconds (after the silence) and soundB starts at 0.2 seconds, you will be doing the equivalent of output[8820] = soundA[4410] + soundB[0]; for sample 8820 and then output[8821] = soundA[4411] + soundB[1]; for sample 8821, etc. As a sound ends (you get to the end of its samples) simply remove it from the 'currently playing' list and keep going until the end of your audio data.
3.4. The simple mixing (sum of samples) described above does have some problems. For example if two samples have values that add up to a number larger than 32767, this cannot be stored in a signed-16-bit number, this is called clipping. For now, just clamp the value to 32767, and get it working... later on come back and implement a simple limiter (see description at end).
Now that you have a mixed version of your track in an uncompressed linear PCM format, that might be enough, so write it to /Documents. If you want to write it in a compressed format, you will need to get the source for an audio encoder and run your linear PCM output through that.
Simple limiter:
Let's choose to limit the top 10% of the sample range, so if the absolute value is greater than 29490 (int limitBegin = (int)(32767 * 0.9f);) we will scale down the value. The maximum possible peak would be int maxSampleValue = 32767 * numPlayingSounds; and we want to scale values above limitBegin to peak at 32767. So do the summation into sampleValue as per the very simple mixer described above, then:
if(sampleValue > limitBegin)
{
float overLimit = (sampleValue - limitBegin) / (float)(maxSampleValue - limitBegin);
sampleValue = limitBegin + (int)(overLimit * (32767 - limitBegin));
}
If you're paying attention, you will have noticed that when numPlayingSounds changes (for example when a new sound starts), the limiter becomes more (or less) harsh and this may result in abrupt volume changes (within the limited range) to accommodate the extra sound. You can use the maximum number of playing sounds instead, or devise some clever way to ramp up the limiter over a few milliseconds.
Remember that this is operating on the absolute value of sampleValue (which may be negative in signed formats), so the code here is just to demonstrate the idea. You'll need to write it properly to handle limiting at both ends (peak and trough) of your sample range. Also, there are some tricks you can do to optimize all of the above during the mixing - you will probably spot these while you're writing the mixer, be careful and get it working first, then go back and refactor/optimize if needed.
Also remember to consider the endian-ness of the platform you are using and the file-format you are writing to, as you may need to do some byte-swapping.
One approach which isn't too hard if your files are stored in a simple format is just to combine them together manually. That is, create a new file with the caf format and manually put together the pieces you want.
This will be really easy if the sounds are uncompressed (linear PCM). But, read the documents on the caf file format here:
http://developer.apple.com/library/mac/#documentation/MusicAudio/Reference/CAFSpec/CAF_spec/CAF_spec.html#//apple_ref/doc/uid/TP40001862-CH210-SW1
I want to add a few bytes of data to a sound file (for example a song). The sound file will be transmitted via radio to a received who uses for example the iPhone microphone to pick up the sound, and an application will show the original bytes of data. Preferably it should not be hearable for humans.
What is such technology called? Are there any applications that can do this?
Libraries/apps that can be used on iPhone?
It's audio steganography. There are algorithms to do it. Refer to here.
I've done some research, and it seems the way to go is:
Use low audio frequencies.
Spread the "bits" around randomly - do not use a pattern as it will be picked up by the listener. "White noise" is a good clue. The random pattern is known by the sender and receiver.
Use Fourier transform to pick up frequency and amplitude
Clean up input data.
Use checksum/redundancy-algorithms to compensate for loss.
I'm writing a prototype and am having a bit difficulty in picking up the right frequency as if has a ~4 Hz offset (100 Hz becomes 96.x Hz when played and picked up by the microphone).
This is not the answer, but I hope it helps.
I'm using Aran Mulhollan' RemoteIOPlayer, using audioqueues in the SDK iphone.
I can without problems:
- adding two signals to mix sounds
- increasing sound volume by multiplying the UInt32 I get from the wav files
BUT every other operation gives me warped and distorted sound, and in particular I can't divide the signal. I can't seem to figure out what I'm doing wrong, the actual result of the division seems fine; some aspect of sound / signal processing must obviously be eluding me :)
Any help appreciated !
Have you tried something like this?
- (void)setQueue:(AudioQueueRef)ref toVolume:(float)newValue {
OSStatus rc = AudioQueueSetParameter(ref, kAudioQueueParam_Volume, newValue);
if (rc) {
NSLog(#"AudioQueueSetParameter returned %d when setting the volume.\n", rc);
}
}
First of all the code you mention does not use AudioQueues, it uses AudioUnits. The best way to mix audio in the iphone is using the mixer units that are inbuilt, there is some code on the site you downloaded your original example from here. Other than that what i would check in your code os that you have the correct data type. Are you trying your operations on Unsigned ints when you should be using signed ones? often that produces warped results (understandably)
The iPhone handles audio as 16-bit integer. Most audio files are already normalized so that the peak sample values are the maximum that fit in a 16-bit signed integer. That means if you add two such samples together, you get overflow, or in this case, audio clipping. If you want to mix two audio sources together and ensure there's no clipping, you must average the samples: add them together and divide by two. Or you set the volume to half. If you're using decibels, that would be about a -6 dB change.