I use on a daily basis MP3s, FLACs, WVs so ability to see all of them on a spectrogram is a must. Read the part where it says about installing the hz_Rolling_Spectrogram.zip to get the UI to stick. See attached screenshot to show how you can save the current window layout and set as the default: It should now remember the UI size until you resize it leaving out the \MAX bit in the parameter. To get fullscreen don't put the program full screen, just drag out the UI window handles to size, close & reopen the app. Then setup mp3tag to work with it in the options and voilà, Spek on juice. Place this unzipped file in: C:\Users yourusername\AppData\Local\sonic-visualiser\Sonic Visualiser\templates and restart the program. I've saved mine and attached it for your use. You can edit the preferences to display 3 Spectrograms (Spectrogram, Melodic Range Spectrogram, Peak Frequency Spectrogram) under the Session template tab and then delete all but the hz Spectrum one and save as a template and you're good to go. Just found a much more advanced Analyser called Sonic Visualiser (Link here) which plays files and the same sort of command will work for it like so: Parameter: '/Q/D/U/C START "SONIC" "C:\Program Files (x86)\Sonic Visualiser\Sonic Visualiser.exe" "'%_path%'"' Parameter: '/Q/D/U/C START "SPEK" /MAX "F:\Music\Spek\spek.exe" "'%_path%'"' EDIT: However, each sector does not represent a specific theory, but it is the result of the intersection of various authors from the previously discussed literature.That thread got a little bloated so this is the working parameters: Name: Spek Each of these sectors represents an aspect of silence analysis based on the ten approaches provided in Chapter 1. In the upper part of Figure 2.1, one can find a circle divided into ten sectors. Most of these aspects are tackled in the third stage of the present analytical method. The three issues that the present chapter purposes to address are: the lack of a larger unified framework in which the ten approaches of Chapter 2 could be combined for the analysis of musical silences, the little importance granted to acoustic silences by mostly relying on the examination of notated silences, or more specifically music rests, and the use of a wide range of terms to refer to relatively similar phenomena. Stage two, description, suggests categories for the durations, dynamics, and timbre of silences, whereas stage three provides tools for analyzing silences in relationship to surrounding rhythm, dynamics, pitch, timbre, and texture, as well as discussing silence’s ability to interact with form, expectations, continuity, evocations, and musical tension. Stage one drafts some procedures for the identification of notated acoustic silences. It comprises three stages: identification, description, and analysis. _ This chapter aims to organize the knowledge acquired in the previous chapter as a method for the analysis of silences. Analysis of Silences in Music: Theoretical Perspectives, Analytical Examples from Twentieth-Century Music, and In-Depth Case Study of Webern’s Op. Listening tests employing a temporal estimation task showed that heavy DRC signals might induce fatigue, though the results were inconclusive. This research shows that decreasing the number of signals interacting under DRC, utilising moderate DRC and applying compression rather than limiting type DRC can reduce the effects of intermodulation distortion, and improve listener enjoyment. Comparative quantitative analysis of simple and compound signal structures under DRC showed some effects from nonlinearity to be the realignment of harmonic signal structures, alteration of instruments’ amplitudes relative to one another, reduction of spectral and temporal clarity, and rearranged dynamic variances related to the rhythmic structure of musical signals. Listening preference tests from this research demonstrate listener inclination for compression being applied to sums of fewer sources, as opposed to compressing signals formed from many sources or subgroups, as is the traditional method for music production. The different DRC configurations were used to examine fatigue and listener preference. In a bid to reduce these nonlinear effects, the point of application, along with the magnitude and type of DRC used in the mixing signal chain was experimented with, reducing the number of signals interacting while under DRC. The nonlinear characteristics of DRC, combined with the interaction of signals once summed, are likely to produce Intermodulation Distortion (IMD), which is unpleasant to hear. This research devised and tested production strategies to improve and reduce the impact of DRC on signals, verified by listener preference. This thesis studied the effects of Dynamic Range Compression (DRC) on audio signals.
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