I am uploading an audacity project with 2 tracks, the 1st one contains a "bitbit" sound resulted from Speex echo cancellation. I tried to remove the sound using Audacity noise cancellation, didn't work. Tried equalizer to cut off some high frequency sounds, worked but somehow degraded the sound quality. Please help how I can clear the noisy audio without significantly degrading quality.
If Audacity doesn't work, any C/C++ library can also be used.
Audacity Project
I think you should use the Noice Reduction effect from the effect menu.
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.
Ok, so I found out that Blender has this really cool video-editing interface and I was beginning to love it. Until, I created this awesome project composition and when I exported the animation as a video file, the audio was out of sync :(.
Actual Problem
Audio is in-sync with video when the animation is played in Blender but is out-of-sync in the rendered video.
Solutions I tried out and failed
I used the 'Audio-Sync' option in the sequencer but that made no difference.
Then I thought that my scene audio frequency might have been an issue since it was initially 48kHz and my videos were at 24kHz, so I changed the scene audio frequency to 24kHz, this still failed to solve the issue.
Initially, I was combining videos with different frame rates and thought that might have been an issue (although animation played as expected in Blender), so I recreated the source videos to ensure all videos I was using in my project had the same frame rate, but this also did not work.
Someone online suggested exporting the video and audio separately and then combining them using a command-line tool like FFMPEG, this also failed.
What's really frustrating
This lag (audio is a few frames ahead of the video) is noticeable only in longer videos (>12 mins, my video is 1 hr long) suggesting a very small rendered rate difference between the video and the audio.
Also, note that the animation plays absolutely fine in Blender, so all I could figure out was that this was a rendering issue.
So if anyone figured this out please let me know. I am a noob in video/audio codecs so please forgive me if I used some incorrect nomenclature above.
I encountered this issue on OBS capture (a 13 minute clip) with Blender 2.93.3. OBS capture is constant framerate at 60 fps, I did try Handbrake conversion to 60 fps constant framerate also with no help. Workaround to solve the issue is to set Blender rendering fps to 59.94, sequencer shows audio track extending over video track but after render everything matches perfectly. Unfortunately you cannot edit the video in 59.94 fps mode, so you need to switch back to 60 fps for editing.
In case your video is 24 fps then use 23.98 fps preset and for 30 fps you can use the 29.97 fps preset.
May 2021. Blender v2.92.0 - I experienced the same as described out-of-sync problem with rendered videos that were over five minutes long. Source was as-is (3.6GB, 10mins) file from Canon EOS 5DMKII, which is an old camera, so pretty much any software can handle the encoding.
In Blender's preview mode everything looks in-sync. Audio and Video tracks are of the same length. I didn't even cut or merged any segments of the source video. I tried running rendering after a clean boot, gave Blender highest resource priority in Win10, allocated more memory to caching, etc. Source and output was on SSD. Rendered result still didn't match what GUI showed. Very frustrating, and a lot of wasted time.
What worked better for me is the following:
Change Video Codec to "FFmpeg video codec #1". This produces a lossless file that is about 27 times bigger (13.8GB for 10mins) than H.264 codec file (0.5GB). However, the audio remains in sync all the way through.
Use HandBrake open source video transcoder to convert FFmpeg file into H.264 (or H.265). End result produces a smallish-size file with A/V that is in sync.
This workaround is relatively painless and produces good-quality results because there's only a single lossy compression step. The time required to get to final file more than triples though. I believe the issue continues to be with the way H.264 rendering in Blender is implemented. I also experienced similar out-of-sync issues in ShotCut a year ago while working with cheap action cam H.265 files. I also found ShotCut to be less stable than Blender.
So after a lot of online searching, I did find an answer to fix this problem, but not in Blender. If you are like me and would like to use Blender for video editing and still get around the issue, then I found a workaround, but you need Shotcut for this. Shotcut is another great free and open-source video editor
Export the entire long video from Blender (the rendered video has desync issues as expected).
Open the video in Shotcut and detach the audio from it.
Use the audio properties to make very fine adjustments to the audio playback speed to suit your requirements (make fine adjustments until video and audio are in sync).
Follow the GIF attached.
(I am using a shorter video in the GIF but you get the idea)
Explanation
Blender has issues while rendering long videos and I noticed that the video is exported at 1.0x speed but the audio is sometimes faster (1.00400x or something like that) and hence the rendered video has audio not in sync with the video.
Another bad thing is that Blender does not really allow very fine playback speed adjustment just to the audio.
One trick is to adjust the pitch of the audio in Blender which in turn changes the playback speed but this is only allowed up to 2 decimal places (not what we want for long videos) and it makes the audio sound funny (since it actually changes the pitch).
Shotcut is a great tool that allows fine playback adjustment, and it also has a pitch compensation feature so that your pitch is kind of unaffected (since we don't want the characters to be sounding funny in our edited video).
Shotcut allows playback speed adjustment up to 6 decimal places.
I landed at this thread because of the same issue happening in a video that I have just finished. The "View animation CTRL F11" command starts an internal player that has sync issues with long videos. Opening the same video file on "Videos" in Fedora, it plays perfectly synchronized.
Recently, I discover that my tutorial videos could be seen at 1.5x playback speed without losses in quality (they are actually better to see, as I normally speak slowly). My problem is that if I change the speed of the video when using a video editor, like Kdenlive, the audio becomes distorted and turns into a mess (higher pitch, I believe).
How could I obtain the same quality as VLC "playback fast" and Youtube "playback speed 1.5" for the audio track? I'm a layman in audio/video editing, so I'm also satisfied with partial answers, like the identification of which terms I should search for in this case.
It might be better to take your audio track and use something like Sound Forge to automatically remove silence. Just be sure to add a pad to that (built into sound forge) otherwise the speech will sound way to chopped and fast.
Aside from that, you could also use Vegas to (then) chop the video to keep pace with your new speech rate. Vegas is a video editing program that is best for this kind of down and dirty editing.
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!
everyone!
I process video from IP cameras and have wrote a motion detection algorithm based on decompressed video analysis. But i really something more fast. I've found several papers about compressed domain analysis but have failed to find any implementations.
Can anyone recommend me some code?
found materials:
http://www.ist-live.org/intranet/school-of-informatics-university-of-bradford001-7/41410206.pdf/view
http://doc.rero.ch/lm.php?url=1000,43,4,20061128120121-NA/Bracamonte_Javier_-_A_Low_Complexity_Change_Detection_Algorithm_20061128.pdf
I had to detect motion in H.264-video, and for me the frame size was a really good indicator.
I used ffprobe (from the ffmpeg project) to export frame sizes like this:
./ffprobe -show_frames -pretty video.mp4 | grep 'size' | grep -o '[0-9]*' > sizes.txt
In my case no movement meant larger I-frames (for me, every 30th frame was an I-frame) and smaller sizes for some of the frames in between.
I'm new to video encoding so I guess these things might be very dependent on encoding and type of video signal, but it's worth a look since it's very fast to try out. Export framesizes and have a look in e.g. Matlab.
Edit:
In the end I re-encoded the video so that every second frame was an I-frame, as this gave better time resolution. One idea I did not test was to reverse the video and do the same thing, this should give more accurate estimations of when the motion started/ended, akin to removing the phase delay by forward-backward filtering.
https://github.com/Breakthrough/DVR-Scan
DVR-Scan is a cross-platform command-line (CLI) application that
automatically detects motion events in video files (e.g. security
camera footage). In addition to locating both the time and duration of
each motion event, DVR-Scan will save the footage of each motion event
to a new, separate video clip. Not only is DVR-Scan free and
open-source software (FOSS), written in Python, and based on Numpy and
OpenCV, it was built to be extendable and hackable.
I can confirm that it works perfectly with MPEG4 (H264) AVI files.
Scanning speed is about 30 fps at my laptop with i5 4300U CPU for 1200x900 video.
You can check the sources for the algorithm used.
And here are some explaning tutorial links from the same author:
https://github.com/Breakthrough/python-scene-detection-tutorial
See also Python scene change detection.