That’s it! Hope you had fun! The documentation in the github repository from Eomys includes even more tutorials. "/Users/philipppaulklose/Desktop/miniDSP Article Sound Quality/kitchenmachineL.wav") Path = "/Users/philipppaulklose/Desktop/miniDSP Article Sound Quality/kitchenmachineL.wav"Īpute_loudness(field_type="free")ĪnalysisSignal.loudness_ot_2D_Data( "/Users/philipppaulklose/Desktop/miniDSP Article Sound Quality/kitchenmachineL.wav",Īpute_level(nb_points=1000,start=0.0,stop=5.2)įrom here we can go straight to the perceived loudness over time with the code: The SPL over time is plotted to understand what is going on in the time domain and to check if analysis boundary times (start and stop times) are right. Start python via the terminal or console via the command “python3”. "/Users/philipppaulklose/Desktop/miniDSP Article Sound Quality/1k_0dBFS.wav",Īs an example, I have recorded a kitchen machine from ca. "/Users/philipppaulklose/Desktop/miniDSP Article Sound Quality/1k_-13dBFS.wav",Īpute_level(nb_points=1000,start=0.0,stop=1) ('/opt/homebrew/lib/python3.9/site-packages/mosqito') To start validation of our measurement system, we use the terminal/shell/powershell and start python via command “python3” and the paste the code: NOTE: You have to change the, path of audio signal for and calibration factor your own analysis! Since REW currently only generates two-channel files (as of now with v5.20.4), the generated file must be split (like the stereo recording done before) into mono files e.g. To control the calibration setup, we generate a sine wave with a level that equates to the level of 94 dBSPL (= -13 dBFS) and max level 107 dBSPL (= 0 dBFS). A 1kHz 0 dBFS input file is interpreted with the used calibration factors as the following dBSPL:Ħ.3 is the cal factor we need in our case, since 0 dBFS in our recording equals 107 dBSPL. Note that if you change your gain on your microphone, that figure will change and the cal factor must be adapted!Ĭalibration must be chosen accordingly to the calibration relation in MOSQITO. It can be found in the bottom row of the app.Ġ dBFS = 107 dBSPL. To find the right calibration factor in MOSQITO, we first need to check in REW the „Peak input before clipping in REW“. Here is the end result at this stage as a wav file you can download here. in ocenaudio via MconvolutionEZ plugin or via the ReaVerb plugin in REAPER) and export with the effect applied. Apply that created filter via a convolution plugin (e.g.It must be applied (burnt-in) directly via convolution into the audio recording. in REW or Dirac Live), the calibration cannot be applied through the import of a text file. Since this not a “regular” frequency range and distortion analysis in the frequency-domain (like it is done e.g. In order to apply the needed calibration to the recorded files, the deficiency correction of the measurement microphone must be applied to the recorded audio signal. With right-click on the recorded file in ocenaudio, split the file to two mono files. MOSQITO can handle different bit depths, but the sample rate must be 48 kHz and one track (mono)! Here, I have recorded a kitchen machine and here is the original file for download. Download and install via pip through the terminal command that can be found here Ĭonnect your equipment and record an audio file. If you need pip, download and find install instructions from This tutorial will show you how to measure the perceived loudness, roughness and sharpness of audio files with MOSQITO and the miniDSP USB microphones. These require their own set of software tools for calculation. For psychoacoustic analysis, a set of metrics like loudness, tonality roughness and sharpness (among others) is being used to describe the sound quality. The human perception works different and is more complex than the parameters we use to describe acoustic and electro-acoustic quality (frequency response, distortion, RT60, etc.). Measuring the psychoacoustic sound quality of audio sources is one of them. Besides that, the microphones can also be used for other interesting purposes! You have probably used your miniDSP microphone(s) for acoustic measurement of loudspeakers and sound equipment. It's a starting point to the exciting field of analyzing Psychoacoustic parameters and we hope you enjoy it! Note that topics/software used here are without any support from the miniDSP support team or the author. Disclaimer: This is an advanced application note requiring knowledge in command line tool usage, convolution and advanced acoustics.
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