I'm trying to perform some basic DSP functions on PCM audio data which I retrieve from a video file using AVAssetReader on the iPhone.
I'm reading the buffers correctly, number of samples per buffer is 8192 (is that by default? can that be changed?).
However, I need to perform windowing, fft and various other manipulations on slices which aren't 8192 samples long. In fact I want to process 512 samples at a time with 50% overlap between each slice.
I've been digging deep in Apple's Accelerate/vDSP framework and I think I can handle the processing and such, just not sure how to actually split up my signal the way I want it.
I have a strong DSP background but unfortunately my DSP programming experience pretty much ends in MATLAB.
Any help will be appreciated.
After digging deeper I found CASpectralProcessor in PublicUtility of the CoreAudio developer tools, which from ver. 4.3 onwards is no longer bundled with XCODE. To download go to
https://developer.apple.com/downloads/index.action?name=for%20Xcode%20-
CASpectralProcessor is exactly what I need, a full blown spectral analyzer that includes customizing window length, window type, hop size. Even performs IFFT with overlap/add!
Hope this helps anyone.
You can chop 1 or 2 of those large buffers into a number of buffers of some shorter desired length and feed those shorter buffers or slices to your processing routine.
Related
I parsed the HEVC stream by simply identifying sart code (000001 or 00000001), and now I am looking for the motion information in the NAL payload. My goal is to calculate the percentage of the motion information in the stream. Any ideas?
Your best bet is to start with the HM reference software (get it here: https://hevc.hhi.fraunhofer.de/svn/svn_HEVCSoftware/trunk/) and add some debug info as the different kinds of data is read from the bitstream. This is likely much easier than writing bitstream decoder from scratch.
Check out the debug that is built into the software already, for example RExt__DECODER_DEBUG_BIT_STATISTICS or DEBUG_CABAC_BINS. This may do what you want already, if not it will be pretty close. I think information about bit usage can be best collected in source/Lib/TLibDecoder/TDecBinCoderCABAC.cpp during decode.
If you need to speed this up, you can of course skip the actual decode steps :)
At the decoder side, You can find the motion vector information as MVD, so you should using pixel decoding process to get the motion information. it need you to understand the process of the inter prediction at HEVC.
than you!
I've been looking for an answer everywhere and I was only able to find some bits and pieces. What I want to do is to load multiple mp3 files (kind of temporarily merge them) and then cut them into pieces using silence detection.
My understanding is that I can use Mp3FileReader for this but the questions are:
1. How do I read say 20 seconds of audio from an mp3 file? Do I need to read 20 times reader.WaveFormat.AverageBytesPerSecond? Or maybe keep on reading frames until the sum of Mp3Frame.SampleCount / Mp3Frame.SampleRate exceeds 20 seconds?
2. How do I actually detect the silence? I would look at an appropriate number of the consecutive samples to check if they are all below some threshold. But how do I access the samples regardless of them being 8 or 16bit, mono or stereo etc.? Can I directly decode an MP3 frame?
3. After I have detected silence at say sample 10465, how do I map it back to the mp3 frame index to perform the cutting without re-encoding?
Here's the approach I'd recommend (which does involve re-encoding)
Use AudioFileReader to get your MP3 as floating point samples directly in the Read method
Find an open source noise gate algorithm, port it to C#, and use that to detect silence (i.e. when noise gate is closed, you have silence. You'll want to tweak threshold and attack/release times)
Create a derived ISampleProvider that uses the noise gate, and in its Read method, does not return samples that are in silence
Either: Pass the output into WaveFileWriter to create a WAV File and and encode the WAV file to MP3
Or: use NAudio.Lame to encode directly without a WAV step. You'll probably need to go from SampleProvider back down to 16 bit WAV provider first
BEFORE READING BELOW: Mark's answer is far easier to implement, and you'll almost certainly be happy with the results. This answer is for those who are willing to spend an inordinate amount of time on it.
So with that said, cutting an MP3 file based on silence without re-encoding or full decoding is actually possible... Basically, you can look at each frame's side info and each granule's gain & huffman data to "estimate" the silence.
Find the silence
Copy all the frames from before the silence to a new file
now it gets tricky...
Pull the audio data from the frames after the silence, keeping track of which frame header goes with what audio data.
Start writing the second new file, but as you write out the frames, update the main_data_begin field so the bit reservoir is in sync with where the audio data really is.
MP3 is a compressed audio format. You can't just cut bits out and expect the remainder to still be a valid MP3 file. In fact, since it's a DCT-based transform, the bits are in the frequency domain instead of the time domain. There simply are no bits for sample 10465. There's a frame which contains sample 10465, and there's a set of bits describing all frequencies in that frame.
Plain cutting the audio at sample 10465 and continuing with some random other sample probably causes a discontinuity, which means the number of frequencies present in the resulting frame skyrockets. So that definitely means a full recode. The better way is to smooth the transition, but that's not a trivial operation. And the result is of course slightly different than the input, so it still means a recode.
I don't understand why you'd want to read 20 seconds of audio anyway. Where's that number coming from? You usually want to read everything.
Sound is a wave; it's entirely expected that it crosses zero. So being close to zero isn't special. For a 20 Hz wave (threshold of hearing), zero crossings happen 40 times per second, but each time you'll have multiple samples near zero. So you basically need multiple samples that are all close to zero, but on both sides. 5 6 7 isn't much for 16 bits sounds, but it might very well be part of a wave that will have a maximum at 10000. You really should check for at least 0.05 seconds to catch those 20 Hz sounds.
Since you detected silence in a 50 millisecond interval, you have a "position" that's approximately several hundred samples wide. With any bit of luck, there's a frame boundary in there. Cut there. Else it's time for reencoding.
I want to get the pitch of a song at any point. I plan on storing the pitches later. How can I read say... an mp3 file or wav file to get the pitch played at a certain point?
Here is a visual example:
Say I wanted to get the pitch that is here at ^this point of the song.
Thanks if you can!
The matter is a tad more complicated than you may be anticipating.
While time-domain approaches exist (that is, approaches which work with the PCM data directly), frequency-domain pitch detection is going to be more accurate. You can read a very simplified overview here.
What you probably want is a Fourier Transform, which can be used to transform blocks of your signal from time-domain to frequency-domain (that is, a distribution of frequency content over a given span of the signal). From there, you would need to analyze the frequency spectrum within that block. The problem becomes even harder still, because there is no best way to deduce pitch from a sampled frequency spectrum in the general case. The aforementioned Wikipedia article should give you a foundation for looking into those algorithms.
Finally, it's worth noting that this is really a language-agnostic question, unless your primary interest is in reading a WAV file specifically using VB.NET.
I am new to CoreAudio, and I would like to output a simple sine wave and square wave with a given frequency and amplitude through the speakers using CA. I don't want to use sound files as I want to synthesize the sound.
What do I need to do this? And can you give me an example or tutorial? Thanks.
There are a number of errors in the previous answer. I, the legendary :-) James McCartney, not James Harkins wrote the sinewavedemo, I also wrote SuperCollider which is what the audiosynth.com website is about. I also now work at Apple on CoreAudio. The sinewavedemo DOES use CoreAudio, since it uses AudioHardware.h from CoreAudio.framework as its way to play the sound.
You should not use the sinewavedemo. It is very old code and it makes dangerous assumptions about the buffer layout of the audio hardware. The easiest way nowadays to play a sound that you are generating is to use the AudioQueue, or to use an output audio unit with a render callback set.
The best and easiest way to do that without files is to prepare a single cycle buffer, containing one cycle of the wave (this is called technically a wavetable)
In the playback function called by CoreAudio thread, fill the output buffer with samples read from the wave buffer.
Note however that you will face two problems very quickly :
- for the sine wave, if the playback frequency is not an integer multiple of the desired sine frequency, you will probably need to implement an interpolator if you want to have a good quality. Using only integer pointers will generate a significant level of harmonic noise.
for the square wave, avoid to just program an array with +1 / -1 values. Such a signal is not bandlimited and will alias a lot. Do not forget that the spectrum of a square wave is virtually infinite!
To get good algorithms for signal generation, take a look to musicdsp.org, that's probably one of the best resource for that
Are you new to audio programming in general? As a starting point i would check out
http://www.audiosynth.com/sinewavedemo.html
This is a minimum osx sinewave implementation by the legendary James Harkins. Note, it doesn't use CoreAudio at all.
If you specifically want to use CoreAudio for your sinewave you need to create an output unit (RemoteIO on the iphone, AUHAL on osx) and supply an input callback, where you can pretty much use the code from the above example. Check out
http://developer.apple.com/mac/library/technotes/tn2002/tn2091.html
The benefits of CoreAudio are chiefly, chain other effects with your sinewave, write plugins for hosts like Logic & provide the interfaces for them, write a host (like Logic) for plugins that can be chained together.
If you don't wont to write a plugin, or host plugins then CoreAudio might not actually be for you. But one of the best things about using CoreAudio is that once you get your sinewave callback working it is easy to add effects, or mix multiple sines together
To do this you need to put your output unit in a graph, to which you can effects, mixers, etc.
Here is some help on setting up graphs http://timbolstad.com/2010/03/16/core-audio-getting-started-pt2/
It isn't as difficult as it looks. Apple provides C++ helper classes for many things (/Developer/Examples/CoreAudio/PublicUtility) and even if you don't want to use C++ (you don't have to!) they can be a useful guide to the CoreAudio API.
If you are not doing this realtime, using the sin() function from math.h is not a bad idea. Just fill however many samples you need with sin() beforehand when it is time to play it, just send it to the audio buffer. sin() can be quite slow to call once every sample if you are doing this realtime, using an interpolated wavetable lookup method is much faster, but the resulting sound will not be as spectrally pure.
There is a good and well documented sine wave player code example in Chapter 7 of the Adamson/Avila "Learning Core Audio" book, published by Addison-Wesley Professional (ISBN-10: 0-321-63684-8 ):
http://www.informit.com/store/learning-core-audio-a-hands-on-guide-to-audio-programming-9780321636843
It is a rather new publication (2012) and addresses precisely the issue of this question. It's only a starting point, but it's a valuable starting point.
BTW. Don't jump to graphs before having this basic lesson (which involves some math) behind.
Concerning example code, a quick and efficient method I often use deals with a pre-filled sinewave lookup table which has as many members as sample rate, for 44100 Hz the table has size of 44100. In other words, cycle length equals sample rate. This gives an acceptable trade-off between speed and quality in many cases. You can initialize it with the program.
If you generate floating point samples (which is default in OSX), and use math functions, use sinf() rather than (float)sin(). Promotions in inner loop cycles of a render callback are always resource-expensive. So are repetitive multiplications of constants, such as 2.0*M_PI, which can too often be found in code examples.
I need a FAST decompression routine optimized for restricted resource environment like embedded systems on binary (hex data) that has following characteristics:
Data is 8bit (byte) oriented (data bus is 8 bits wide).
Byte values do NOT range uniformly from 0 - 0xFF, but have a poisson distribution (bell curve) in each DataSet.
Dataset is fixed in advanced (to be burnt into Flash) and each set is rarely > 1 - 2MB
Compression can take as much as time required, but decompression of a byte should take 23uS in the worst case scenario with minimal memory footprint as it will be done on a restricted resource environment like an embedded system (3Mhz - 12Mhz core, 2k byte RAM).
What would be a good decompression routine?
The basic Run-length encoding seems too wasteful - I can immediately see that adding a header setion to the compressed data to put to use unused byte values to represent oft repeated patterns would give phenomenal performance!
With me who only invested a few minutes, surely there must already exist much better algorithms from people who love this stuff?
I would like to have some "ready to go" examples to try out on a PC so that I can compare the performance vis-a-vis a basic RLE.
The two solutions I use when performance is the only concern:
LZO Has a GPL License.
liblzf Has a BSD License.
miniLZO.tar.gz This is LZO, just repacked in to a 'minified' version that is better suited to embedded development.
Both are extremely fast when decompressing. I've found that LZO will create slightly smaller compressed data than liblzf in most cases. You'll need to do your own benchmarks for speeds, but I consider them to be "essentially equal". Both are light-years faster than zlib, though neither compresses as well (as you would expect).
LZO, in particular miniLZO, and liblzf are both excellent for embedded targets.
If you have a preset distribution of values that means the propability of each value is fixed over all datasets, you can create a huffman encoding with fixed codes (the code tree has not to be embedded into the data).
Depending on the data, I'd try huffman with fixed codes or lz77 (see links of Brian).
Well, the main two algorithms that come to mind are Huffman and LZ.
The first basically just creates a dictionary. If you restrict the dictionary's size sufficiently, it should be pretty fast...but don't expect very good compression.
The latter works by adding back-references to repeating portions of output file. This probably would take very little memory to run, except that you would need to either use file i/o to read the back-references or store a chunk of the recently read data in RAM.
I suspect LZ is your best option, if the repeated sections tend to be close to one another. Huffman works by having a dictionary of often repeated elements, as you mentioned.
Since this seems to be audio, I'd look at either differential PCM or ADPCM, or something similar, which will reduce it to 4 bits/sample without much loss in quality.
With the most basic differential PCM implementation, you just store a 4 bit signed difference between the current sample and an accumulator, and add that difference to the accumulator and move to the next sample. If the difference it outside of [-8,7], you have to clamp the value and it may take several samples for the accumulator to catch up. Decoding is very fast using almost no memory, just adding each value to the accumulator and outputting the accumulator as the next sample.
A small improvement over basic DPCM to help the accumulator catch up faster when the signal gets louder and higher pitch is to use a lookup table to decode the 4 bit values to a larger non-linear range, where they're still 1 apart near zero, but increase at larger increments toward the limits. And/or you could reserve one of the values to toggle a multiplier. Deciding when to use it up to the encoder. With these improvements, you can either achieve better quality or get away with 3 bits per sample instead of 4.
If your device has a non-linear μ-law or A-law ADC, you can get quality comparable to 11-12 bit with 8 bit samples. Or you can probably do it yourself in your decoder. http://en.wikipedia.org/wiki/M-law_algorithm
There might be inexpensive chips out there that already do all this for you, depending on what you're making. I haven't looked into any.
You should try different compression algorithms with either a compression software tool with command line switches or a compression library where you can try out different algorithms.
Use typical data for your application.
Then you know which algorithm is best-fitting for your needs.
I have used zlib in embedded systems for a bootloader that decompresses the application image to RAM on start-up. The licence is nicely permissive, no GPL nonsense. It does make a single malloc call, but in my case I simply replaced this with a stub that returned a pointer to a static block, and a corresponding free() stub. I did this by monitoring its memory allocation usage to get the size right. If your system can support dynamic memory allocation, then it is much simpler.
http://www.zlib.net/