Im new to NAudio but the goal of my project is to provide the user with the ability for the user to listen to an MP3 and then select a sample or a "chunk" of that song as a sample which could be saved to disk. These samples would be able to replayed at the same time (i.e. not merged but played at the same time).
Could someone please let me know what the overall strategy required to achieve this (....not necessarily the specifics...almost like pseduo code....).
For example would the samples / chunks of a song need to be saved as a WAV file. And these samples could be played together in the WAV format, etc.
I have seen a few small examples of a few implementations of some of the ideas Ive mentioned above but dont have a good sense of the big picture just yet.
Thanks in advance,
Andrew
The chunks wouldn't need to be saved as WAV files unless you were keeping them for future use. You can store the PCM audio (Mp3FileReader automatically converts to PCM) in a byte array and use RawSourceWaveStream to play them.
As for mixing them, I'd recommend using the MixingSampleProvider. This does mean you need to convert your RawSourceWaveStream to IEEE float, but you can use Pcm16BitToSampleProvider to do this. This will give the advantage that you can adjust volumes (and do other DSP) easily on the samples you are mixing. MixingSampleProvider also auto-removes completed inputs, so you can just add new inputs whenever you want to trigger a sound.
Related
I am trying to implement TTS. I have just read about wavenet, but, I am confused on local conditioning. The original paper here, explains to add a time series for local conditioning, this article explains that adding mel spectrogram features for local conditioning is fine. As we know that Wavenet is a generative model and takes raw audio inputs to generate high audio output when conditioned,
my question is that the said mel spectrogram features are of that raw audio passed as in the input or of some other audio.
Secondly, for implementing a TTS the audio input will be generated by some other TTS system whose output quality will be improved by wavenet, am I correct to think this way??
Please help, it is direly needed.
Thanks
Mel features are created by actual TTS module from the text (tacotron2 for example), than you run vocoder module (Wavenet) to create speech.
It is better to try existing implementation like Nvidia/tacotron2 + nvidia/waveglow. Waveglow is better than wavenet between, much faster. Wavenet is very slow.
My question is with respect to a labVIEW VI (2013), I am trying to modify. (I am only just learning to use this language. I have searched the NI site and stackoverflow for help without success, I suspect I am using the incorrect key words).
My VI consists of a flat sequence one pane of which contains a while loop where integer data is collected from a device and displayed on a graph.
I would like to be able to be able to buffer this data and then send it to disk when a preset number of samples have been collected. My attempts so far result in only the last record being saved.
Specifically I need to know how to save the data in a buffer (array) then when the correct number of samples are captured save it all to disk (saving as it is captured slows the process down to much).
Hope the question is clear and thanks very much in advance for any suggestions.
Tom
Below is a simple circular-buffer that holds the most recent 100 readings. Each time the buffer is refilled, its contents are written to a text file. Drag the image onto a VI's block diagram to try it out.
As you learn more about LabVIEW and as your performance and multi-threaded needs increase, consider reading about some of the LabVIEW design patterns mentioned in the other answers:
State machine: http://www.ni.com/tutorial/7595/en/
Producer-consumer: http://www.ni.com/white-paper/3023/en/
I'd suggest to split the data acquisition and the data saving in two different loops using a producer/consumer design pattern..
Moreover if you need a very high throughput consider using TDMS file format.
Have a look here for an overview: http://www.ni.com/white-paper/3727/en/
Screenshot will definitely help. However, some things are clear:
Unless you are dealing with very high volume of data, very slow hard drives or have other unusual requirements, open the file before your while loop, write to it every time you acquire a sample (leaving buffering to the OS), and close it afterwards.
If you decide you need to manage buffering on your own, you can use queues. See this example: https://decibel.ni.com/content/docs/DOC-14804 for reference (they stream data from disk, buffering it in the queue, but it is the same idea)
My VI consists of a flat sequence one pane of which
Substitute flat sequence for finite state machine (e.g. http://forums.ni.com/t5/LabVIEW/Ending-a-Flat-Sequence-Inside-a-case-structure/td-p/3170025)
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 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.