Im currently struggling to understand what is happening. So, I created a sound using the audiowrite function in Matlab (the sound is created using two different sounds but I dont think it matters) first with a sampling frequency of 44100 Hz, and another one, the sound file is the same but the sampling frequency is 48000 Hz. Now I'm observing that the sound produced at 44100Hz is approx. 30sec longer than the other one (48000Hz sampling). It looks like phase shifting of some sort, but I'm not sure. Any help/explanation is appreciated. I also made a amplitude/time plot for better understanding:
(I set the x axis to 350sec to see where the signal ends).
EDIT: here is the code for how I create the sound file:
[y1,F1] = audioread(cave_file); %cave and forest files are mp3 files loaded earlier both have samp.freq of 48000Hz
[y2,F2] = audioread(forest_file);
samp_freq=44100;
%samp_freq=48000;
a = max(size(y1),size(y2));
z = [[y1;zeros(abs([a(1),0]-size(y1)))],[y2;zeros(abs([a(1),0]- size(y2)))]]
audiowrite('test_sound.wav', z,samp_freq);
What is the storage format? More specifically, is the info about sampling rate and number of channels stored in file meta data? which is then used during playback.
If so, then there are 3 possibilities for this behavior:
1) The sampling rate meta data of the 44.1KHz file is incorrect, while the audio was sampled at the correct rate i.e. 44.1KHz. Because the 44.1KHz file is playing longer than 48KHz, which I'm assuming to be producing the correct sound, and playing for the correct duration, it can be concluded that the sampling rate meta data of 44.1KHz is much lesser than 44.1KHz.
Could you please check the meta data? or attach the files here so that I can try to take a look?
2) The sampling didn't happen at the correct rate, while the meta data has 44.1KHz as the sampling rate.
3) The number of channels is incorrectly stored.
In case the files are raw PCMs, then this probably the correct sampling rate and/or number of channels is not selected when playing the 44.1KHz file.
Hope this helps
Related
I have a wav file pulled up in MATLAB, and I can see it's sample rate. All I need to do is change this 1 number. Everything else in the file will remain uncahnged. (The resulting sound would play at a different speed but would have an identical array of sample data.)
The reason I need to do this is because MATLAB seems to freak out when I tell it to open something sampled at anything other than 8k. All I need MATLAB for is to edit the file, so the sample rate really doesn't matter at all, since I'll be putting it back into a wav file when I'm done. So I either need to be able to change the value in the wav file that stores the sample rate, or to get MATLAB to change the sample rate it prefers from 8k to the sample rate that my files were recorded at.
if you just want to change the sampling frequency, here is the code, but it would distort the original wav file. If you decrease the sampling frequency, then the beat and music would be very slow.
Code:
[y, fs, nbits]=wavread('stego_lab');
fs2=11025;
wavwrite(y,fs2,nbits,'stego2_lab.wav');
sound(y,fs2,nbits)
you can hear it but the samples will remain the same.
Hope it helps.
There is the SOX tool, which should help you in that respect, and it comes on almost any platform - http://sox.sourceforge.net
There is also libsndrate, libsamplerate, libsndfile and others, that might have executables too.
Try this solution
[x,fs] = wavread('infile.wav');
<br>[p,q] = rat(16000/fs) % to convert to 16k sample rate</br>
<br>y = resample(x,p,q); % signal package require
wavwrite(x,16000,'outfile.wav');
How is it possible to encode black/white picture into ".wav"-file? I know that it is possible for sure with help of "stenography". But I don't know it's algorithms. What algorithms exist? And what books/sources are the best for understanding of their principles?
Edited:
Actually I have stereo wav-file. My task is to decode pictures from it. The task says, that frequencies of the left channel show the X-coordinate, frequencies of the right channel show the Y-coordinate of Cartesian coordinate system. These points compose the picture with the text-message. So, I must to write programm for this. I haven't any idea what should I do.
Probably the simplest version of steganography using a wav file would be to use 16-bit samples in the wave file, but only dedicate the 15 most significant bits to sound. In the least significant bit of each sample, you'd encode one pixel of your black and white picture.
Regenerating the picture would require software to open the wave file, take the least significant bit from each sample, and put those bits back together with each other into (for example) a JPEG file.
To put things into perspective, a CD has two channels containing 16 bit samples at a rate of 44.1 KHz, so you'd only need the LSBs from around 10 seconds of sound to encode a fairly typical full-color JPEG (e.g., 100KB or so). A wave file of a typical ~3 minute pop song could hide around 15-20 full-color pictures pretty easily.
Edit: (to reply to edited answer). This is a little tougher to deal with. An individual sample can't represent any frequency; it just represents the amplitude at a given point in time. To get frequency, you need a number of samples over a period of time -- and you need to know the exact period to convert.
Once you know that, you basically do an FFT on the samples. That will tell you the relative strengths of signal at all possible frequencies. Presumably, you'd pick the strongest one and scale appropriately. Do the same for the other channel and draw a pixel at that point.
Your ears are not sensitive to small changes in sound file.
Wav files are UNCOMPRESSED data so its just a file of 16-24bit characters. Your ears cannot notice slight differences betweeen bits. All you need to do is periodically inject bit values that represent an image in the data.
So if you insert one pixel for every 1000 data points you can hide an image (without even encrypting it) in a wave file. If a user plays the file they CANNOT hear it.
When you save the file on your computer or computer afar you can use a decoding tool that is aware of the hiding techinque.
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.
Is it possible to compare two sounds ?
for example app have already a sound file mp3 or any format, is it possible to compare any static sound file and recorded sound inside of app ?
Any comments are welcomed.
Regards
This forum thread has a good answer (about three down) - http://www.dsprelated.com/showmessage/103820/1.php.
The trick is to get the decoded audio from the mp3 - if they're just short 'hello' sounds, I'd store them inside the app as a wav instead of decoding them (though I've never used CoreAudio or any of the other frameworks before so mp3 decoding into memory might be easy).
When you've got your reference wav and your recorded wav, follow the steps in the post above :
1 Do whatever is necessary to convert .wav files to their discrete- time
signals:
http://www.sonicspot.com/guide/wavefiles.html
2 time-warping might or might not be necessary depending on difference
between two sample rates:
http://en.wikipedia.org/wiki/Dynamic_time_warping
3 After time warping, truncate both signals so that their durations are
equivalent.
4 Compute normalized energy spectral density (ESD) from DFT's two signals:
http://en.wikipedia.org/wiki/Power_spectrum.
6 Compute mean-square-error (MSE) between normalized ESD's of two
signals:
http://en.wikipedia.org/wiki/Mean_squared_error
The MSE between the normalized ESD's
of two signals is good metric of
closeness. If you have say, 10 .wav
files, and 2 of them are nearly the
same, but the others are not, the two
that are close should have a
relatively low MSE. Two perfectly
identical signals will obviously have
MSE of zero. Ideally, two "equivalent"
signals with different time scales,
(20-second human talking versus
5-second chipmunk), different energies
(soft-spoken human verus yelling
chipmunk), and different phases
(sampling began at slightly different
instant against continuous time
input); should still have MSE of zero,
but quantization errors inherent in
DSP will yield MSE slightly greater
than zero.
http://en.wikipedia.org/wiki/Minimum_mean-square_error
You should get two different MSE values, one between your male->recorded track and one between your female->recorded track. The comparison with the lowest difference is probably the correct gender.
I confess that I've never tried to do this and it looks very hard - good luck!