A spectrogram is a visual representation of the spectrum of frequencies of a signal as it varies with time. When applied to an audio signal, spectrograms are s...

Foobar users , next time you listen to AFX , look at the spectrogram , cool abstract art.

Digital sound drawing

Scotty H created this spectrographic animation of a classic dial-up modem's startup noise. Here's a breakdown, by Oona Räisänen, of what each section concerns:

LightningChart JS Interactive Examples. Fastest JavaScript Charts: Create High-Performance Scientific Charts, Precision for Medical Charts, Spectrograms, 2D Charts, 3D charts, Heatmaps as Spectrograms.

Is there Matlab code that shows a series of numbers representing a waveform as a spectrogram? The time interval each sample represents is the same, idearly this could also be given to use for the ...

Sound frequencies are displayed as they are heard. Lower frequencies are mapped low (bottom) to high (top). Brightness is determined by amplitude. Sweeping tones and rhythmic patterns create intricate structures. The circular form is in memorial of dead formats; the CD, MiniDisc and others. R.I.P. Here’s a Leesa’s The Mansion run through Spectrogram: Built by … Continue reading "Spectrogram – Canvas based Musical Spectrum Analysis"

Learn the practical information behind a FFT, PSD, and spectrogram for vibration analysis. Download real world vibration data and MATLAB analysis scripts.

Read this short post if you want to be like Neo and know all about the Mel Spectrogram!

Today we're going to be making the spectrogram visualization I demonstrated in my Automated Video Editor video. This post has an accompanying video, if you'd like to follow along with it as well. A spectrogram is a way to view how an audio spectrum changes over time. Spectrum meaning the range of frequencies or tones…

Modified sox to try doing logarithmic frequency scaling on the spectrogram output..

Audio Spectrogram Creator creates a customisable spectrogram from an audio file

spectrogram of super trouper

Spectrogram of humpback whale vocalizations

Create a real-time audio spectrogram visualizer using a Raspberry Pi Pico, digital microphone and LCD display. Find this and other hardware projects on Hackster.io.

University of Bologna student Pier Luigi Forte designed and built meshwave, a laser cut sculpture that expresses the structure of music in 3D. Forte created the design by transforming spectrogram…

Fig. 2. Neural network projections of birdsong vocalizations into a 2D latent space. (A) A scatter plot where each point in 2D space represents a syllable sung by a Cassin’s vireo (library acquired from Hedley, 2016). Colors denote hand labeled syllable categories, which tend to cluster in the low-dimensional space. The 5 9 5 grid in the lower right quadrant marks the locations of samples drawn from the 2D space. (B) Spectrograms of synthetically generated syllables, corresponding points in the 5 9 5 grid in (A), where each spectrogram is produced by projecting the 2D points into the decoder network. (C) A similar uniform grid, sampled from a 2D plane of a different neural network trained on European starling song. Signals generated from each point in the grid are presented to a different starling trained on a same-different operant conditioning task. Distances between points on the grid, and thus the overall warping, reflect an empirically measured similarity between neighboring syllables. (D) A plot of transitions between syllable clusters in a 2D space similar to (A) but from a single European starling; transitions between sequential elements are shown as lines. Line color shows the relative time of a syllable transition within a bout; later transitions are darker. - "Five Ways in Which Computational Modeling Can Help Advance Cognitive Science: Lessons From Artificial Grammar Learning"

Description Figure 1: SeisSound sample image This data product (for a sample click image on right or to visit SeisSound data product repository, click here ) conveys the data in four different ways: an image of the original seismogram an image of a filtered version of the seismogram an image of the spectrogram of the filtered trace an audio playback of the seismic signal that is time-compressed and amplitude-normalized so that the sound is audible for human ears (roughly 20 Hz – 20 kHz) The temporal evolution of the seismogram is depicted by the seismogram turning from a light gray color to a dark black color as time evolves. A pink vertical line in each of the sub-plots indicates the current time of the playback, as does the time counter in the upper right. The SeisSound data products do not reproduce the seismograms in true time, as this would make the movies too long and boring to listen to because the sound would be out of our hearing range. Instead the playback is sped up by the factor indicated in the x-label. For example, a speed up factor of 500 will transform the frequencies 0.5 to 40 Hz in the seismogram to 250 (0.5*500) Hz to 20,000 (40*500) Hz range of our hearing. What’s your hearing range? Test it and find out here. Both the spectrogram and audio file are created after applying a 0.5 Hz high-pass filter. To hear the full range of sounds we recommend listening to these data products with earbuds or good speakers. It is difficult to transform seismic data in a way that both the high-frequency and low-frequency signals become audible at the same time. This is because each would require a different speed-up factor to make the signals heard. To solve this problem we apply an appropriate speed-up factor to hear the higher-frequency (>0.5 Hz) energy and then use MATLAB’s voltage controlled oscillator (vco) function to create a sound signal that oscillates around an audible center frequency in proportion to the amplitude of the seismogram’s lower-frequency energy 1 . We make the length of this modulated signal identical to the time-compressed higher-frequency channel. This allows us to save these two sound outputs as a stereo sound pair 2 . The stereo sound from these dual frequency bands, in combination with the video images, allows the correlations between the lower-frequency surface-waves and high-frequency triggered earthquakes and tremor signals (if they exist) to be assessed. The color of the spectrogram indicates amplitude, where warm colors are higher amplitudes and cool colors are lower amplitudes. These amplitudes represent the log base 10 of the normalized amplitude, multiplied by a scale factor of 10. All SeisSound data products have the same scaling so comparisons can be made between products. Information about the earthquake is displayed in the first line of the title, and information about the seismic recording station, and its distance and azimuth to the earthquake, is shown in the second line of the title. Listed in the top y-axis label is the type of seismogram (i.e., velocity) and the seismogram’s channel code (i.e., BHZ). There is an option to show seismic wave phase arrival times, which are indicated with short blue vertical lines and associated blue text that displays the phases (i.e., P, S, SKS, R1). Exporting the audio channel of the SeisSound product for an event to the corresponding ground motion visualization (GMV) product produces an interesting composite movie. Click on the image below to see and hear such a composite movie created for the Sea of Okhotsk M8.2 event of May 24, 2013. In this case the audio was played only 102 times faster than true speed in order to stay in sync with the video presentation. The following table summarizes the parameters used to generate the SeisSound data product. PARAMETER SAMPLE VALUE Filter 0.5 Hz high-pass VCO filter 0.5 Hz low-pass Speed Factor 500 Approximate number of Frames requested for the movie 100 Image/Movie height (pixels) 720 P slowness (s/degree) 7.2 Rayleigh slowness (s/degree) 28.5 List of requested seismic phases P, Pn, Pg, Pdiff, pPdiff, sPdiff, PcP, PP, PP, PS, PKP, SKS, S, Sn, Sg, Sdiff, pSdiff, sSdiff, SP, ScS, SS, R1, R2 Number of seconds between two consecutive phases to avoid overprinting phase markers (second) 600 IRIS ID (links to information about the earthquake) 1916079 (26 December 2004; Sumatra; magnitude 9) Station Network IU Station name DGAR Station Channel BHZ Script Bundle To create customized SeisSounds, download the MATLAB script bundle (please read the installation instructions in this README file before installing). Footnotes [1] To do this we modulate the amplitude (volume) of the vco tone by the sum of two envelope functions. The first is the envelop of the full data trace and the second is the envelop of the data trace after a low-pass filter (<0.5 Hz) has been applied. We find that using the sum of these two envelopes we can highlight both the arrival of the largest amplitudes in the seismogram in addition to the arrival of higher frequency energy. [2] This is accomplished using MATLAB’s wavwrite function.