My Go-to commercial VSTs

Some time ago, I wrote an article about the free VSTs that I like to use. This time I will present my favorite commercial VSTs. No, this is not yet-another-post on Serum or Diva. In fact, I felt no reason to join the others for them, since I find much more powerful some of the following than Serum, and I own several analog hardware synths, that makes the need for synths of the type of Diva obsolete.

How many soft synths can someone use in a medium sized track? I would say unlimited, since one could create any kind of layering, or modular combinations (more about that, later).

This is a countdown, presenting the synths I actually use the most. To complete the following list, I would add that sometimes two free VSTs join my commercial ones in my production: Surge and Odin2. But let us go back to our topic.

Here is my top-ten, in reverse order of popularity:

#10. Steinberg Padshop: Although a synth that "comes with the DAW", padshop is very useful, and quick for, you guessed, pads (it's only that Rapid, after 1.8 update, is faster with granular synthesis, so Padshop has a strong competitor here).

#9. Waldorf Largo: Do I need some good brass, without the need to open the Virus? Largo will give me that, and others. People nowdays dislike non-vector synths (even a free synth, Surge, has a vector face). Well, good for me, because then I could get Largo with 75% discount.

#8. Synthmaster One: A very nice sounding synth, helps to build quickly support lines, and comes with excellent libraries.

#7. Thorn: Beautiful synth, quick synthesis, stunning glitches, it offers me synthesis in areas not covered by others. Really. I use it a lot.

#6. Wiggle: Yes, yes, and yes. The Chinese synth is an amazing instrument, with unlimited possibilities. Whenever I need to create a "different" sound, that I know it will attract attention, I just wiggle.

#5. Melda MPowersynth: Although this theoretically is part of MSoundFactory (more about that later), by its own is a very powerful synth and the most easy to use when doing additive synthesis (I do a lot, since I commonly need to invent new plucks for each new track). 3%-5% of the stems have MPowersynth.

#4. Arturia Pigments: The Arturia masterpiece is a brilliant synth, but quite heavy as compared with others, and as such does not find the recognition it deserves in my mixes. But its terrific arpeggiator is always a bonus to my tracks.

#3. Synthmaster 2.9: This "little" synth keeps growing and maturing. It has stunning sound quality. It is not higher in the rank mainly due to its details and rather not-so-stremlined workflow, that make sometimes editing a sound a bit tedious task.

#2. Parawave Rapid: This anti-Serum is by far a superior synth than Serum, having an incredible number of features, being continuously in development, and providing the most efficient way for sound design. It is #2 only because of the outwordly capabilities of the synth that is on #1. Rapid is nowadays around 30%-40% of instances.

#1. Melda MSoundFactory: do not think that its price is high; actually it is really discounted for its abilities. Ladies and gentlemen, this is the King of the soft synths: a modular synth that does everything and in a very fast way (comparatively to its complexity). How about running 10 instances of MPowersynth inside MSoundFactory? And that's only the beginning. Super efficient and super fast. Nearly 50% of the soft instances are MSoundFactory in my projects.

An extra mention to my principal soft drum machine: This is Melda MDrummer, an incredible drum power station. I have incorporated all my samples to it, and nowadays its streamlined processing quickens significantly my workflow.

Honorary mention goes also to Sektor, Vaporizer 2 and Codex, three wavetable synths that I commonly don't use (I find Sektor having ugly FX, Vaporizer having an unfamiliar interface and Codex very limited), but I chose to have them and to keep them, and from time to time, they find their way into my mixes. Also mention goes to Vacuum Pro and Retrologue, which compete for the same, analog-ish, position, the first for the quick buttons (and NOT for its voice doubler) and the second for its depth.

COVID-19 - how many got infected, but never recorded as such?

We all know some friends who underwent the covid-19, without ever been officially recorded as such. We all know also that extensive testing may result close to having the actual number of the covid-19 cases. Therefore, as the data available are enriched by the tests applied to every country (from https://www.worldometers.info/coronavirus/), I did an estimation of the number of real patients from covid-19.




The countries considered are the ones with the highest number of patients (excluding china, which has not released number of tests).

Here is the status as of today:

The next chart is revealing how Germany has demonstrated an outstanding testing approach considering the rest countries.

At x-axis is the tests/pop, at y-axis is total deaths. We keep this information for later.

The basic assumption is that we will use the number of deaths as a de facto knowledge on covid-19 spread. Some deviations exist, but most deaths from covid-19 are recorded well.

The number of Patients reported from every country will be a derivative.

The next table shows the tests committed per total death. It is a sign of “sensitivity” of a country over the expansion stage of the virus. The highest the number, the more precise the results expected.

The next table is the diagnosis of patients per test (e.g. the inverse of tests committed per one positive case). We will keep the number of Germany for later, because it has demonstrated a high number of tests over the lowest number of deaths (see previous table).

Now it comes the first assumption. The next table shows an intermediate value of assumed tests done at the rate of Germany. Why Germany? From the above results, we will use Germany as a model country for doing much in an early stage of the virus (which has also the lowest coverage, as we will see in a following table). The formula for the following table is Population_Country X (tests_GER/Population_GER).

Note that the above number of assumed tests does not take into account the stage on which the testing takes place. We will adjust the above value by using the following two tables. The first table shows the deaths/population for each country. I call this “tolerance”. It corresponds to a de facto social pressure.

Then, for each country, we will calculate their “relative tolerance”, their ratio as above over the ratio in Germany. It shows the magnification of the consequences of covid-19 in a country, over Germany’s one, when late/limited testing is applied - it is used as a "temporal" adjuster (disclaimer: some countries went early in the game, and no knowledge on extensive testing existed, but still, the ratio reflects the temporal magnitude). In other words, the following value transforms any country into a "German-minded" one, in terms of the virus testing. The table is as follows:

We will then multiply the above values with the intermediate assumed tests, to calculate how many tests would have been committed if the sensitivity was the one of Germany.

Now, you remember the table above, termed “diagnosis of patients per test”? We will use the value of Germany to calculate the number of patients. This assumes that if a country had done tests at the pace of Germany, they would have achieved the same rate of diagnosis. Note that Germany has the lowest value, e.g. the most tests per patient. I repeat that table for convenience here:

If we multiply the “assumed tests per sensitivity” table, with the value of Germany for “diagnoses: patients/test”, we get the following estimate for the actual number of patients per country, i.e. including cases which have never been tested. I include also the patients recorded. Note that, again, the calculation assumes Germany being “ideal”, as the calculation produces a number equal the reported number of patients in Germany, i.e. if we assume that Germany “loses” patients, these values should be higher for all (but unfortunately, I haven’t any idea to calculate how much). Also, another factor that messes up real patient data are the different policies applied. Being just a model estimate, the next table does not aim but capture the effect created by late/limited testing on a country. The first column is my estimation on actual cases (equals to "patients out there" + recorded), the second column is what is recorded as of today.

Notes:

• Germany is selected as "clean" case for the following reasons:

1. Extensive testing in absolute values ,only second to US
2. Extensive testing in relative to population values, only second to Italy
3. Lowest patients/tests, allows considering a "limit" on diagnosing
4. Lowest "tolerance" (see above), allows for estimation due to "scientific" interest, rather than as a consequence of social pressure.

• The above factors present Germany as the most "clean" case. The more "dirty" you consider Germany (e.g. inaccurate in estimating the real number of patients), the worse scores are assumed for the rest countries.
• I received feedback by an Iranian friend that the reported number of deaths is much lower than the real one. I promised to check on their time series data, and try to spot any faking (by comparing with other countries). To be continued, there...

Conclusion

This is a model on how much could have been revealed to other countries, should they have used the approach of Germany. It is not a blame game, as late knowledge was available for Germany to take measures, but only to give an idea on a potential number of positive covid-19 cases, based on the present number of deaths.

PS. Some people insist on believing that in Germany the low death scores are because "it is the young people who get the disease". Really? Have you thought maybe that the many deaths in Italy in contrast, could be an outcome of many-many more cases who have never been reported?