I'm doing a puzzle that gets me to call a phone number which produces a load of
beeping sounds. Putting this into audacity as a spectrogram produces this: image
Zoomed in it looks like this: image2
This looks like On Off Keying. The problem is i don't know how to take this binary signal and convert it into actual binary (other than doing it by hand but yikes). So far GNU radio seems to be promising but I'm not tooooo sure on how to achieve what I'm looking for with it.
Thanks.
edit - Here's the waveform zoomed in zoomed out
The overall recording is also low quality - the original is taken from calling a phone number which transmits this sound - getting a high quality recording of that call would also prove helpful.
https://drive.google.com/file/d/1l2RaZiVVYkF_SXvRsTH8lsvnq3GYKEWQ/view?usp=sharing - google drive link to the wav file
Related
My Zoom H4n somehow decided it didn't want to properly save two recordings this weekend, leaving me with four zero byte files (which I have tried any which way to open/convert, but nothing was working).
I then used CardRescue to scan the SD card for any audio it could find, and - lo and behold - I got .wav files! However, instead of two files for each session (one was an XLR output from the desk, the other the on-Zoom mics), or even a nice stereo with one left, the other right, I have a mess.
In importing as raw data to Audacity (the rescued .wavs themselves do not open), the right channel has the on-Zoom mic audio, with intermittent silence. The left has the on-Zoom audio, followed by the same part of the XLR input audio. This follows the same pattern as the silences.
I have spent hours chopping up in Garageband, but as it is audio for a video, it needs to match what 'really' happened perfectly (I appreciate for a podcast/audio-only I could relatively simply take away the on-Zoom mic audio from the left channel). I began attempting to sync the mic audio to the on-camera audio (which, despite playing around with settings is as unusable as it always is) but because it's a pattern, can't help but wonder if there's a cleaner fix: either analysing the audio somehow as there are clean lines if I look at the spectral data, or a case of adding a couple of numbers to the wav's binary that'd click the two into place?
I've tried importing to Audacity with different settings, different offsets - this has ended up in either slow audio, fast audio, or heavily distorted audio (but always the same patterns with the files).
I use a Mac (and don't know any PC users close by!) so any software suggestions will need to run on Mac. However, I'm willing to try just about anything that's not dragging tiny clips.
How to get file information like sampling rate, bit rate etc of .raw audio files using terminal in linux? Soxi works for .wav files but it isn't working for .raw.
If your life depended on discovering an answer you could make some assumption to tease apart the unknowns ... however there is no automated way since the missing header would give you the easy answers ...
The audio analysis tool called audacity allows you to open up a RAW file, make some guesses and play the track
http://www.audacityteam.org
In audacity goto File -> Import -> Raw Data...
Above settings are typical for audio ripped from a CD ... toy with trying stereo vs mono for starters.
Those picklist widgets give you wiggle room to discover the format of your PCM audio given that the source audio is something when properly rendered is recognizable ... would be harder if the actual audio was noise
However if you need a programmatic method then rolling your own solution to ask those same questions which appear in above window is possible ... is that what you need or will audacity work for you ? We can go down the road of writing code to play off the unknowns mentioned in #Frank Lauterwald's comment
To kick start discovering this information programmatically, if the binary raw audio is 16 bit then each audio sample (point on the audio curve) will consume two bytes of your PCM file. For mono audio then the following two bytes would be your next sample, however if its stereo then these two following bytes would be the sample from the other channel. If more than two channels then just repeat. Typical audio is little endian. Sampling rate is important when rendering the audio, not when programmatically parsing raw bytes. One approach would be to create an output file with a WAV header followed by your source PCM data. Populate the header with answers from your guesswork. This way you could listen to this output file to help confirm your guesses.
Here is a sample 500k mono PCM audio file signed 16 bit which can be imported into audacity or used as input to rolling your own identification code
The_Constructus_Corporation_Long_Street-ycexQvMy03k_excerpt_mono.pcm
How system can improve a video quality automatically? For example, a dark line on my face in video can't be removed by system automatically...make sense. Here I'm trying to understand Azure Media Services encoding permutations.
When I uploaded a 55.5 MB mp4 file and encoded with "H264AdaptiveBitrateMP4Set720p" encoder preset, I received following output files:
Now look at green rectangular highlighted video file, this looks good according to input file size. But if you look at red rectangular highlighted video files, these are improved files for adaptive streaming, which looks useless if you compare with my example 'a dark line on my face'. Here's my questions and I would love to read your input on this:
What are exact reasons encoder increases the file size?
Why I should pay more for bandwidth and storage on these large files, how I convince clients?
Is there any way I can define not to create such files when scheduling encoding?
Any input is highly appreciated.
1) The dark lines appearing on your face have nothing to do with encoding. Encoding simply means re-arranging bits that make up the video using a different compression algorithm than the one used in the source video.
2) As you see from the filenames of the files generated, they all have a different bitrate, denoted in kbps. This is the amount of data, i.e. number of bits, that the transcoder has to decode to get 1-second worth of video footage. The higher the bit-rate, the better is the quality of the video because there is more detail such as better light and color information stored in every pixel and hence in every frame of such a video.
As a corollary, a higher-bit rate video is suited better for faster internet connections.
So, Azure must have converted from your source video, these 4 different videos of different bit-rates, all having the same video (h.264) and audio (AAC) encoding.
3) As to how to let Azure not make so many files, I do not know the answer to that. I am pretty sure it will be some configuration somewhere but I honestly have no idea. I am confident, though, that it is only a matter of some configuration to tell it to stop doing the other bit-rate conversions.
In summary:
a) to clear off the dark thingy on your face in the video, you have to edit the source video in a video editor and that has nothing to do with video encoding.
b) The file sizes are different due to different bit-rates, meaning differences in light and color information, i.e. shadow detail, stored in every pixel of every frame of the video footage.
Those users who have a faster Internet connection, to them you could show the option of downloading a higher-bit-rate file. The higher bit-rate file will show slightly better quality even under the same video resolution, i.e. 720p in your case.
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 using pygame to play .wav files and want to change the pitch of a particular .wav file as each level in my game progresses. To explain, my game is a near copy of the old Oric1 computer OricMunch Pacman game, where there are a few hundred pills to be munched on each level, and for every pill that is munched a short sound is played, with the pitch of the sound increasing slightly for each pill eaten/munched.
Now here is what I have tried:
1) I have used pythons wave module to create multiple copies of the sound file, each newly created file having a slight increase in pitch (by changing the 3rd parameter in params() the framerate, sometimes referred to as the sample frequency) for each cycle of a for loop. Having achieved this, I could then within the loop create multiple sound objects to add to a list, and then index through the list to play the sounds as each pill is eaten.
The problem is even though I can create hundreds of files (using the wave module) that play perfectly with their own unique pitches when played using windows media player, or even pythons winsound module, pygame does not seem to interpret the difference in pitch.
Now interestingly, I have downloaded the free trial version of Power Sound Editor which has the option to change the pitch, and so I’ve created just a few .wav files to test, and they clearly play with different pitches when played in pygame.
Observations:
From printing the params in my for loop, I can see that the framerate/frequency is changing as intended, and so obviously this is why the sounds play as intended through windows media player and winsound.
Within pygame I suspect the reason they don’t play with different pitches is because the frequency parameter is fixed, either to the default settings or via the use of pygame.mixer.pre_init, which I have indeed experimented with.
I then checked the params for each .wav file created by the Power Sound Editor, and noticed that even though the pitch sound was changing, the frequency stayed the same, which is not totally surprising since you have to select 1 of 3 options to save the files, either 22050, 44100 or 96000Hz
So now I thought time to check out the difference between pitch and frequency specifically in relation to sound, since I thought they were the same. What I found was it seems there are two principle aspects of sound waves: 1) The framerate/frequency And 2) The varying amplitude of multiple waves based on that frequency. Now I far from clearly understand this, but realise the Power Sound Editor must be altering the shape/pitch of the sound by manipulating the varying amplitude of multiple waves, point 2) above, and not by changing the fundamental frequency, point 1) above.
I am a beginner to python, pygame and programming in general, and have tried hard to find a simple way to change sound files to have gradually increasing pitches without changing the framerate/fundamental frequency. If there’s a module that I can import to help me change the pitch by manipulating the varying amplitude of mutiple waves (instead of changing the framerate/sample frequency which typically is either 22050 or 44100Hz), then it needs to take relatively no time at all if being done on the fly in order to not slow the game down. If the potential module opens, changes and then saves sound files, as opposed to altering them on the fly, then I guess it does not matter if it’s slow because I will just be creating the sound files so I can create sound objects from them in pygame to play.
Now if the only way to achieve no slow down in pygame is to create sound objects from sound files as I have already done, and then play them, then I need a way to manipulate the sound files like the Power Sound Editor (again I stress not by changing the framerate/sample frequency of typically 22050 or 44100) and then save the changed file.
I suppose in a nut shell, if I could magically automate Power Sound Editor to produce 3 to 4 hundred sound files without me having to click on the change pitch option and then save each time, this would be like having my own python way of doing it.
Conclusion:
Assuming creating sound objects from sound files is the only way not to slow my game down (as I suspect it might be) then I need the following:
An equivalent to the python wave module, but which changes the pitch like Power Sound Editor does, and not by changing the fundamental frequency like the wave module does.
Please can someone help me and let me know if there’s a way.
I am using python 3.2.3 and pygame 1.9.2
Also I’m just using pythons IDLE and I’m not familiar with using other editors.
Also I’m aware of Numpy and of various sound modules, but definitely don’t know how to use them. Also any potential modules would need to work with the above versions of python and pygame.
Thank you in advance.
Gary Townsend.
My Reply To The First Answer From Andbdrew Is Below:
Thank you for your assistance.
It does sound like changing the wave file data rather than the wave file parameters is what I need to do. For reference here is the code I have used to create the multiple files:
framerate = 44100 #Original .wav file framerate/sample frequency
for x in range(0, 25):
file = wave.open ('MunchEatPill3Amp.wav')
nFrames = file.getnframes()
wdata = file.readframes(nFrames)
params = file.getparams()
file.close()
n = list(params)
n[0] = 2
n[2] = framerate
framerate += 500
params = tuple(n)
name = 'PillSound' + str(x) + '.wav'
file = wave.open(name, 'wb')
file.setparams(params)
print(params)
file.writeframes(wdata)
file.close()
It sounds like writing different data would be equivalent or similar to how the Power Sound Editor is changing the pitch.
So please can you tell me if you know a way to modify/manipulate wdata to effectively change the pitch, rather than alter the sample rate in params(). Would this mean some relatively simple operation applied to wdata after it’s read from my .wav file. (I really hope so) I’ve heard of using numpy arrays, but I have no clue how to use these.
Please note that any .wav files modified in the above code, do indeed play in Python using winsound, or in windows media player, with the pitch increase sounding as intended. It’s only in Pygame that they don’t.
As I’ve mentioned, it seems because Pygame has a set frequency (I guess this frequency is also sample rate), that this might be the reason the pitch sounds the same, as if it wasn’t increased at all. Whereas when played with e.g. windows media player, the change in sample rate does result in a higher sounding pitch.
I suppose I just need to achieve the same increase in pitch sound by changing the file data, and not the file parameters, and so please can you tell me if you know a way.
Thank you again for helping with this.
To Summarise My Initial Question Overall, Here It Is Again:
How do you change the pitch of a .wav file without changing the framerate/sample frequency, by using the python programming language, and not some kind of separate software program such as Power Sound Editor?
Thank You Again.
You should change the frequency of the wave in your sample instead of changing the sample rate. It seems like python is playing back all of your wave files at the same sample rate (which is good), so your changes are not reflected.
Sample rate is sort of like meta information for a sound file. Read about it at http://en.m.wikipedia.org/wiki/Sampling_rate#mw-mf-search .
It tells you the amount of time between samples when you convert a continuous waveform into a discrete one. Although your (ab)use of it is cool, you would be better served by encoding different frequencies of sound in your different files all at the same sample rate.
I took a look at the docs for the wave module ( http://docs.python.org/3.3/library/wave.html ) and it looks like you should just write different data to your audio files when you call
Wave_write.writeframes(data)
That is the method that actually writes your audio data to your audio file.
The method you described is responsible for writing information about the audio file itself, not the content of the audio data.
Wave_write.setparams(tuple)
"... Where the tuple should be (nchannels, sampwidth, framerate, nframes, comptype, compname), with values valid for the set*() methods. Sets all parameters... " ( also from the docs )
If you post your code, maybe we can fix it.
If you just want to create multiple files and you are using linux, try SoX.
#!/bin/bash
for i in `seq -20 10 20`; do
sox 'input.wav' 'output_'$i'.wav' pitch $i;
done