Im back with another questions about freeswitch.
The default sending frequency from freeswitch is 8000. So when i record an piece of the stream the frequency of the mp3 (or wav) is also 8000. What i need is a higher frequency.
All that i found is an variable:
<action application="set" data="record_sample_rate=44100" />
I added it to the extension but it doesn't change anything. (44100 is not my must have frequency. But higher than 8000 where great). Maybe if this is not possible, do you guys thinks that change the frequency over python is a great idea?
Hope somebody knows a trick to realize that.
Freeswitch always uses the same frequency for recording as the one of the channel that is recorded. This way, it is the most economical way to do recording without extra real-time work for the CPU.
You can upsample the wav file later, with specialized audio conversion tools in low priority.
And hey, this question belongs to serverfault, not to stackoverflow.
I use "sox" now for resampling the audio file. You can execute the commandline tool in the script. When somebody knows another function or method in freeswitch for sending in another frequency please tell me
Related
What I want is to be able to get a signal at my raspberry pi at home when I'm not at home so I can e.g. wake up my PC. I always have an old phone lying around that I never really use. So I thought, I can call my phone, a specific mp3 ringtone plays, my raspberry pi listens and recognizes the ringtone and therefore the signal. So I can pretty much chose whatever ringtone I want (but hopefully a not too long one). But the problem is, that it should be recognizable by the raspberry and it should be distinguishable from other sounds. At best I can play random music at home and it will not get signalled until it's the specific ringtone i chose.
So I'm at the very beginning of the project and I have a lot of question. Is this even feasible? How do I listen to the ringtone? Should I use a normal microphone or could I e.g. trigger some gpio pin as long as a specific frequency is played? What kind of ringtone should I use to be as distinguishable as possible? And how to create the software to recognize the sound?
I know this is a lot and I don't expect a step by step solution. But maybe you got some hints to get me in the right direction?
If someone has a similar problem, I found a solution: First I had to choose between a mostly hardware solution and a mostly software solution. The hardware solution is to filter specific frequencies. This seems to be pretty hard using normal band-pass filters if you want narrow bands. There are also components that can do that, now I know of the NE567. But this component only reacts to one frequency and takes quite a lot of energy. To recognize a ringtone, more of these components are needes which means more power consumption. Additionally this solution is pretty unflexible.
So I went for the software solution. Now I have an Arduino Uno that gets an amplified electret microphone signal at an analog input pin. The data is collected and simultaneously analysed with an FFT algorithm. Then I check the dominant frequency if there is any and safe it in an array. Everytime a got a new data point I compare the array with the pattern of my ringtone and calculate a score for the match. If the score is big enough the ringtone is "found" and I can trigger my event.
I'm actually pretty pleased with the solution because it works quite well even with the phone some feet away from the microphone. I thought I need to put the microphone almost directly next to the phone to get good results, but I dont have to. It's still a little sensitive, because the sound volume shouldnt be too high or to low. But with the right volume settings it works with a quite big area when the phone is in the same room. It works even better with some space between microphone and phone, because the phones radiation from the call seems to disturb the circuit quite a lot. There is also the problem, that other noises block the ringtone recognition. I could compensate that with my algorithm, but I almost used up all resources of the Arduino, so I had to keep the algorithm simple. But in my case I dont have a noisy environment, so this is not a problem for me. Another pro is that my event was never triggered from another sound and it seems almost impossible that this could happen by accident.
So it is feasible and I think its actually a quite elegant solution. I also thought about a vibration detection or even directly using the vibration motor's signal but I have no control over the vibration function of that old phone. But I can chose the ringtone for every contact, so I only gave the "magic" ringtone to myself and so the event can only be triggered by myself. I only have to say, that writing the software was kind of hard with the Arduinos limitations. Because I need the data in real time I have limited time for the calculation. I had to limit the incomping data and therefore I can only listen to frequencies up to 10kHz. But the ringtone recognition is still possible and I think it was worth the effort. :)
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.
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'm looking for a program that is able to recognize individual audio samples from my computer and reroute them to trigger WAV files from a library. In my project, it would need to be realtime as the latency would not be a desired result. I tried using dictation software that would recognize words to trigger opening a file and that's the direction where I want to go, but instead of words I want it to be sounds and it would happen in realtime. I'm not sure where to go and am just looking for some guidance. Does anyone have any suggestions of what I should do?
That's a fairly broad question, but I can tell you how I would do it. (Hardly the only way, but where I would start.)
If you're looking for real time input, the Java Sound library (excellent tutorial here) allows for that. (Just note that microphone input from a web page is difficult on anything, due to major security concerns, so this would be a desktop application.)
If it needs to be real time, the first thing I would suggest is stream and multithread the hell out of it. I would suggest the Java 8 Stream API, but since you're looking for subsamples that match a specific pattern, then each data point will have to be aware of the state of its neighbors, and that isn't easy with streams.
You will probably want to know if a sound roughly resembles an audio profile, so for that, I would pick a tolerance on just how close you want it to be for a match (remembering that samples may not line up 100% anyway, so "exact" is not an option), and then look up Hidden Markov Models. I suggest these because they're what voice recognition software typically uses, and while your sounds may not be voices, it will give you an idea of what has already been done.
You'll also want to maintain a limited list of audio samples in memory. Specifically, you will likely need the most recent data, because an audio signal is a time-variant signal, and you can't get a match from just one point. I wouldn't make it much longer than the longest sample you're looking to recognize, as audio takes up a boatload of memory.
Lastly (for audio), I would recommend picking a standard format for comparison. Make it as good as gets you decent results, and start high. You will want to convert everything to that format before you compare it.
Once you recognize a specific sound, it's basically a Command Pattern. Specific sounds can be mapped, even with a java.util.HashMap, to specific files, which (if there are few enough) you might even have pre-loaded.
Lastly, it's worth looking at the Java Speech API. It's not part of the JDK and it's quite dated, but you might get some good advice from its implementation.
This is of course the advice of a Java-preferring programmer, but I imagine that there might be some decent libraries in Python and Ruby to help you as well; and of course there's something in C somewhere. This may sound like a lot, but most of the material is already implemented and ready-to-go.
Hopefully this helps, let's look forward to other answers.
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.