I am quite new to LabVIEW and NI devices.
I am working on Active Noise Cancellation Project, where I will be using two microphones input and one loud speaker as output. I have NI myRIO 1900 and CDAQ 9178 devices in our university lab. I need to do real time audio processing, I will collect data from microphone and process it using filtered XLMS algorithm to produce anti noise from loud speaker and other microphone is error microphone. I want to process data so quickly( within 1.7 msec ) so I will have real time response at 44100 sample rate !! My question is , 'is it possible to do with labview ?? and is stream processing possible in labVIEW?? and can I achieve so small audio latencies as mentioned above ??'
I have searched for audio processing objects in labview help. I can only find 'Acquire Sound', 'Play Waveform', surprisingly 'Acquire Sound configuration ' will work only for duration of minimum of 1 second not less than that !!! I can't input the time milli seconds !!!( I am still facing problem installing myRIO, so I have used host computed VI to do this.)
Please help !! Thank You
The thing you should be looking into is the FPGA part of the myRIO. You’re never going to be able to get 1.7ms response time via the host computer. The FPGA can access the Analogue inputs and outputs, so if you can get your algorithm to compile onto the FPGA then it should work.
Yes, it is possible with LabVIEW, insofar as any algorithm you want to code up can be executed by LabVIEW. If you're asking whether there is a library that already exists to do the filtering you're wanting to do, you may want to explore the NI Sound & Vibration toolkit, which is sold separate from LabVIEW, or explore third-party libraries.
The raw waveform mathematics abilities that come with LabVIEW are fairly extensive. You should be able to code whatever transforms you want if you know the base math.
Related
I have recorded an audio.
I dont know how it happened that only one sided speech is recorded and the other speech is recorded with a very low sound.
Is there any solution to amplify the other side signal.
any help would be much appreciated.
This question is probably more appropriately asked at a forum where recording and mixing is discussed. For example: https://sound.stackexchange.com/
The ideal would be to improve your recording situation, to control factors so the sound are more closely matched. (Match microphones, isolate the speakers from environmental sounds, optimize input levels, etc.)
After that, the next option or step is to pre-process your audio files with a tool like Audacity. Use this or another DAW (Digital Audio Workstation) tool to match amplitudes or employ noise filtering or a range of other tools.
Audio processing is both tricky (an "art") and cpu intensive, so it's good to get as much of this handled as possible before the sounds are imported into a program.
I have a situation where I have a video capture of HD content via HDMI with audio from a sound board that goes through a impedance drop into a microphone input of a camcorder. That same signal is split at line level to a 'line in' jack on the same computer that is capturing the HDMI. Alternatively I can capture the audio via USB from the soundboard which is probably the best plan, but carries with it the same issue.
The point is that the line in or usb capture will be much higher quality than the one on HDMI because the line out -> impedance change -> mic in path generates inferior quality in that simply brushing the mic jack on the camera while trying to change the zoom (close proximity) can cause noise on the recording.
So I can do this today:
Take the good sound and the camera captured sound and load each into
audacity and pretty quickly use the timeshift toot to perfectly fit
the good audio to the questionable audio from the HDMI capture and
cut the good audio to the exact size of the video. Then I can use
ffmpeg or other video editing software to replace the questionable
audio with the better audio.
But while somewhat quick and easy, it always carries with it a bit of human error and time. I'd like to automate this if possible as this process is repeated at least weekly throughout the year.
Does anyone have a suggestion if any of these ideas have merit or could suggest another approach?
I suspect but have yet to confirm that the system timestamp of the start time may be recorded in both audio captured with something like Audacity, or the USB capture tool from the sound board as well as the HDMI mpeg-2 video. I tried ffprobe on a couple audacity captured .wav files but didn't see anything in the results about such a time code, but perhaps other audio formats or other probing tools may include this info. Can anyone advise if this is common with any particular capture tools or file formats?
if so, I think I could get best results by extracting this information and then using simple adelay and atrim filters in ffmpeg to sync reliably directly from the two sources in one ffmpeg call. This is all theoretical for me right now-- I've never tried either of these filters yet-- just trying to optimize against blind alleys by asking for advice up front.
If such timestamps are not embedded, possibly I can use the file system timestamp for the same idea expressed in 1a, but I suspect the file open of the two capture tools may have different inherant delays. Possibly these delays will be found to be nearly constant and the approach can work with a built-in constant anticipation delay but sounds messy and less reliable than idea 1. Still, I'd take it, if it turns out reasonably reliable
Are there any ffmpeg or general digital audio experts out there that know of particular filters that can be employed on the actual data to look for similarities like normalizing the peak amplitudes or normalizing the amplification of the two to some RMS value and then stepping through a short 10 second snippet of audio, moving one time stream .01s left against the other repeatedly and subtracting the two and looking for a minimum? Sounds like it could take a while, but if it could do this in less than a minute and be reliable, I suspect it could work. But I have only rudimentary knowledge of audio streams and perhaps what I suggest is just not plausible-- but since each stream starts with the same source I think there should be a chance. I am just way out of my depth as to how to go down this road, so if someone out there knows such magic or can throw me some names of filters and example calls, I can explore if I can make it work.
any hardware level suggestions to take a line level output down to a mic level input and not have the problems I am seeing using a simple in-line impedance drop module, so that I can simply rely on the audio from the HDMI?
Thanks in advance for any pointers or suggestinons!
I am developing a software which can auto record and extract every words in my voice. I used portaudio library to solve it. But I am stuck on detecting the sound: I set the silence's value is zero so if there is a sample which is zero, it must be a start or end point of a sound. But when I ran it, the program created many words. I think because the value I read by portaudio is raw data, so it can't be processed like that. Am I right? How can I fix it? By the way, I am coding in C++ :D
To detect the presence of a signal in a PCM stream you be able to detect it. As dprogramz put said, the noise floor of your soundcard is probably not perfect and so there will be some noise signal recorded (even with no mic connected).
The solution is to use a VOX or VAD algorithm to detect the presence of your voice. VOX can be tricky, since in most consumer grade electronics the noise floor is just low enough to be "silence" to the human ear, relative to the signal. This means that the difference on amplitude between the noise floor and signal may be slight. If your sound card has AGC turned on this can make it even more difficult, since the noise floor may move. Having said that, VOX can be implemented successfully on consumer grade equipment. It just takes more effort to establish the threshold. When done best the threshold is calculated periodically while the stream is active.
If I were doing this I'd implement a VAD algorithm. Since your objective is to detect your voice this should provide a reliable result regardless of the equipment you use.
I don't think it's because it is a RAW value. RAW sound files are a bitstream of frequency and volume information.
However, the value will rarely (if ever) be zero. You have to take into account there is a small amount of electrical noise that is made by the mic. Figure out the "idle" dB of your mic (just test the level when you aren't talking into it). You Then need to set a silence threshold (below a certain dB level for a certain number of samples) to detect the beginning/end. Attempting to detect a zero value is gonna be near impossible.
I am currently thinking about what I could do to measure the time it takes from the point where the computer gets audio input (through a normal audio input on a soundcard) to the point where there's something to work with, e.g. noise cancellation or something like that.
The main problem I reckon is to measure when the audio signal was created and the synchronization of the sender and receiver.
So far I came up with the following ideas:
Use the serial port to transmit timing information
Put a timestamp into the audio signal
Transmit a recurring signal - a delay would be visible
Do you have more ideas or something that I m not seeing in mine? I thought I would find more academic work on this matter but was sad to see that this is not the case, am I searching wrong?
you can check the latency in windows with this tool they also have some great info on the site also you can read up on the ASIO drivers or try to reach out to the communities that use these tools (DJs Guitar modeling scene) another great source of information is open Source projects like JACK that have more technical information:
Latency Tool:
http://www.thesycon.de/deu/latency_check.shtml
Asio Wikipedia Page:
http://en.wikipedia.org/wiki/Audio_Stream_Input/Output
Guitar Amp Modeling:
http://www.guitarampmodeling.com/
JACK Project homepage:
http://jackaudio.org/
Hope that helps.
I'm wondering what is the recommended audio library to use?
I'm attempting to make a small program that will aid in tuning instruments. (Piano, Guitar, etc.). I've read about ALSA & Marsyas audio libraries.
I'm thinking the idea is to sample data from microphone, do analysis on chunks of 5-10ms (from what I've read). Then perform a FFT to figure out which frequency contains the largest peak.
This guide should help. Don't use ALSA for your application. Use a higher level API. If you decide you'd like to use JACK, http://jackaudio.org/applications has three instrument tuners you can use as example code.
Marsyas would be a great choice for doing this, it's built for exactly this kind of task.
For tuning an instrument, what you need to do is to have an algorithm that estimates the fundamental
frequency (F0) of a sound. There are a number of algorithms to do this, one of the newest and best
is the YIN algorithm, which was developed by Alain de Cheveigne. I recently added the YIN algorithm
to Marsyas, and using it is dead simple.
Here's the basic code that you would use in Marsyas:
MarSystemManager mng;
// A series to contain everything
MarSystem* net = mng.create("Series", "series");
// Process the data from the SoundFileSource with AubioYin
net->addMarSystem(mng.create("SoundFileSource", "src"));
net->addMarSystem(mng.create("ShiftInput", "si"));
net->addMarSystem(mng.create("AubioYin", "yin"));
net->updctrl("SoundFileSource/src/mrs_string/filename",inAudioFileName);
while (net->getctrl("SoundFileSource/src/mrs_bool/notEmpty")->to<mrs_bool>()) {
net->tick();
realvec r = net->getctrl("mrs_realvec/processedData")->to<mrs_realvec>();
cout << r(0,0) << endl;
}
This code first creates a Series object that we will add components to. In a Series, each of the components
receives the output of the previous MarSystem in serial. We then add a SoundFileSource, which you can feed
in a .wav or .mp3 file into. We then add the ShiftInput object which outputs overlapping chunks of audio, which
are then fed into the AubioYin object, which estimates the fundamental frequency of that chunk of audio.
We then tell the SoundFileSource that we want to read the file inAudioFileName.
The while statement then loops until the SoundFileSource runs out of data. Inside the while
loop, we take the data that the network has processed and output the (0,0) element, which is the
fundamental frequency estimate.
This is even easier when you use the Python bindings for Marsyas.
http://clam-project.org/
CLAM is a full-fledged software framework for research and application development in the Audio and Music Domain. It offers a conceptual model as well as tools for the analysis, synthesis and processing of audio signals.
They have a great API, nice GUI and a few finished apps where you can see everything.
ALSA is sort of the default standard for linux now by virtue of the kernel drivers being included in the kernel and OSS being depreciated. However there are alternatives to ALSA userspace, like jack, which seems to be aimed at low-latency professional type applications. It's API seems to have a nicer API, although I've not used it, my brief exposure to the ALSA API would make me think that almost anything would be better.
Audacity includes a frequency plot feature and has built-in FFT filters.