If you're not bored to tears - I'd be happy to grab whatever audio you need when I get home from work this evening to help do a proper differential FR. When the stylus runs across the groove it creates these straight clicks across the entire frequency range, usually at higher amplitude at the lower frequencies, but not always. The right channel of the same sample had 4 distinct pops from a scratch on the record, and so it was used to evaluate how each preamp handeled those pops.įrom the spectrogram data in post #6 I showed that the groove noise is variable due to the nature of record playback. Sound Quality Supports 16-bit, 24-bit and 32-bit. Export your recordings in many different file formats, including multiple files at once. Export / Import Import, edit, and combine sound files. The Local Natives samples (FFT.txt labeled files) were pulled apart and used to evaluate record noise because the left channel had only two single notes across the sample (spectro from post #6) and I figured I could have a good look at groove noise and resolution of those notes. Recording Audacity can record live audio through a microphone or mixer, or digitize recordings from other media. System noise was evaluated by simply recording each system into audacity with nothing playing but energized. My goals were to evaluate three areas: System Noise, Gain, and Record Noise (groove distortion, clicks, pops) using different samples of music for the Gain evaluation (Pearl Jam) and Record noise (Local Natives). Should I zoom in on it, out? I used the waveform data to measure the gain of each pop for comparison and recorded that, however apart from subjective listening, I didn't know what more objective data, from the tools I have, could be obtained from the handling of pops by each preamp. However, at looking the pops on the spectrogram, I needed some input on what, if anything can be obtained from the spectral data. In the default Waveform View, loud clicks often show up as easily seen spikes, but smaller, lower amplitude clicks can be very hard to find without zooming in to near sample level then scrolling the. One of my favorite LP's (for which this sample was taken) I discovered had somehow gotten a scratch on it and while bad for listening was good for testing pops. Click removal using the Spectrogram view is a workflow tutorial giving steps to remove hard-to-spot clicks using Audacitys Spectrogram View view. 30db difference when the samples were taken? I'd say some, but I don't know to what extent. I know from comparing the two spectrogram for each channel for each preamp, there is, what appears to me, noticeably more background noise on the PREII and at a higher db vs the MM-6. I was exploring if that could be demonstrated in spectral data as well. For this particular analysis I was exploring: Does one preamp handle record noise better? What frequency range does inherent record noise live at? We know from the review of the PREII by it had low headroom (22mv input) before clipping. Using the commandline program is a bit tedious, and also the need to convert all your images prior to the resynthesis is also tiresome.Īdding a capability to read major image formats (JPG, PNG) and convert them to grayscale automatically would be great.Īlso R,G, B and A channels of an image file could be treated as separate audio channels this way - color of the pixels would translate to the stereo image of the sound (pun intended).Sorry dc, I was inquiring what *could* be gleaned from a spectrogram and how to properly interpret what is shown. Have you ever tried pixelating a spectrgram or sharpening it to listen to the results? Being able to export the spectrograms out can be great too, because you can convert a sound into an image, then process the image with image-specific tools and then resynthesize the sound back. Importing image files and synthesizing sound out of them would be a super cool thing. To spot such noise open the spectrogram and expand it as much as possible so that you have a better view of the frequencies. Some options have no effect, or a different effect, when the Pitch (EAC) algorithm. The options in this window apply to the Spectrogram View in the Audio Track Dropdown Menu. I think it might be a great idea to use the code and make this program a part of Audacity's toolset. Accessed by: Edit > Preferences > Spectrograms (on a Mac Audacity > Preferences > Spectrograms ) Click in the left column for other preferences. I used that tool when to design some sound effects for games, and it is a very unique tool, giving you abilities that no synthesizer provides. It has some limitations - the input image has to be a specific type of BMP file, and it's a rather barebone commandline tool - however it does the job and allows users to convert image files into sound files. ARSS is an opensource commandline program that can produce high quality black&white spectrograms, but more importantly: it can chew up images and synthesize sounds treating these images as spectrograms.
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