![]() The Auger & Flandrin paper instead comes from a world that summarises a spectrogram as a two-dimensional Wigner-Ville distribution filtered with a smoothing window leading to a time-frequency representation of the Cohen’s class. The language used in a publication like the DAFx book is typical in this world. There is nothing particularly mathematical about the implementation of this, and any intuition used by the programmer is a mixture of the visual and techniques from the world of engineering. The smoothing window is because your Fourier transform - a thing which matches up sinusoids of different frequencies against a signal to identify which ones would add up to it - operates on an infinite signal, consisting of the input you give it repeated forever in both directions: this will have a discontinuity each time it wraps around, and the smoothing window removes some of the frequency artifacts from these discontinuities. The short slices are because you want a fixed, smallish number of output bins, and you have various tradeoffs - time and frequency resolution and computational efficiency - to consider in that. For a programmer, a spectrogram comes from taking short overlapping slices of a sampled signal, multiplying each by a smoothing window shape, applying a short-time Fourier transform, and taking the magnitudes of the complex output bins to get one column of the spectrogram per slice of input. I have since realised this is partly because it isn’t all that clear with its notation, but there is also a big gap between the naive programmer’s view (that’s mine) of a spectrogram and the mathematical analysis used in the paper. I read this paper about 15 years ago and didn’t understand it. Version reviewed: 1.7.Illustration from Auger & Flandrin (1995) In conclusion: Sonic Visualiser is a free and powerful audio analyzer that gives an average control based on graphical waveforms and spectograms. Pluses: free, support for plugins, you can add annotations, detailed paramters display, use of colors to point out your remarks ĭrawbacks/flaws: suitable for musicians with average computers knowledge Sonic Visualiser is not supporting original VST plugins, but you can get use the Audacity VST Enabler that works for the Mac or Windows version. ![]() You can also use different colors for any selection or annotation. For any observation you can add annotations directly to the waveform with a pin-point precision thanks to the zoom option. ![]() You can also visually apply the spectrum over the spectogram and view its modification while playing the audio track. In case is activated, the spectogram will be displayed on the bottom of the window and you can browse it simultaneously with the waveform. The whole designed is focused on displaying the waveform and its timeline, with its correspondent layers sorted on tabs on the right. A simple restart will enable the new plugin installed and Sonic Visualiser is ready for a deeper analyzing process. Some of them are ready to be installed, others have to be copied to the Vamp Plugins directory which has to be created manually. You just have to access the correspondent library and choose the proper plugin. The Windows users will be in advantage, as they can also use LADSPA plugins from the Audacity plugins library. Being an open source project, Sonic Visualiser can use LADSPA and DSSI plugins. You can load any audio file (WAV, Ogg and MP3) and view their waveforms or spectograms and analyze in standard parameters its content. ![]() Sonic Visualiser is a free visualizer and analyzer of the sound waveform and specter. Either, Linux, MacOSX, or Windows user, Sonic Visualiser is available in any of your correspondent operating system. In case you work in the music business, or you study in this field, Sonic Visualiser may come in handy if you want to analyze in detail the contents of an audio file. In this way, music has reached a new dimension, in which anyone can analyze it into a deeper perspective. Today, composing, recording, producing and performing, involves new techniques and tools most of them depending on the PC's power. From the beginning of the digital era, music has changed a lot.
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