[sdiy] Measuring Roughness, Sharpness, Tonality, Fluctuation Strength, Stationary Loudness, and Time-Varying Loudness, was: VCF caps in modern synths

[Michael E Caloroso]

Neat.  I am a LabVIEW expert and am looking for work in this field.

MC

On 3/28/21, cheater cheater <cheater00social at gmail.com> wrote:
> BTW, if anyone wants to know how to measure Roughness. It's a fairly
> new concept in psychoacoustics which seems to have first been
> published about in 1985 in German and in 1997 in English (see
> references in [1] which cite [2] and [3]). A more detailed description
> of an algorithm is described in [4]. Roughness is part of a bunch of
> other novel psychoacoustical measurements which seem in specific to be
> great tools for anyone working with sound or music, and would probably
> be very popular, if every last deadbeat wasn't trying to monetize
> knowledge. There's a bunch of them described in documentation for the
> National Instruments Sound and Vibration Measurement Suite, a LabVIEW
> suite which implements those measurements [5] which I copy in below.
> Finally, Mattias Rickardsson brings up a nice overview of roughness
> measurement in [6].
>
> [1] Martin Pflueger, Robert Höldrich, Franz Brandl, Werner Biermayer:
> Psychoacoustic measurement of roughness of vehicle interior noise,
> 1999
> https://www.researchgate.net/publication/243523940_Psychoacoustic_measurement_of_roughness_of_vehicle_interior_noise
> [2] W. Aures: Ein Berechnungsverfahren der Rauhigkeit, Acustica Vol.
> 58, 1985, pp268-281, Paywalled here for $30:
> https://www.ingentaconnect.com/contentone/dav/aaua/1985/00000058/00000005/art00005
> [3] P. Daniel, R. Weber: Psychoacoustical Roughness: Implementation of
> an optimized Model. - Acoustica Vol. 83, 1997, pp 113-123, Paywalled
> here for $30:
> https://www.ingentaconnect.com/contentone/dav/aaua/1997/00000083/00000001/art00020
> [4] R. Hoeldrich: An Optimized Model for the  Objective Assessment of
> Roughness Sensations in Vehicle Noise, free at:
> https://iem.kug.ac.at/fileadmin/media/iem/altdaten/projekte/publications/paper/pub_avlpaper/pub_avlpaper.pdf
> [5] National Instruments: Sound Quality Algorithms (2020)
> https://www.ni.com/de-at/support/documentation/supplemental/08/sound-quality-algorithms.html
> [6] Sound Modulation Metrics: Fluctuation Strength and Roughness
> (2020)
> https://community.sw.siemens.com/s/article/sound-modulation-metrics-fluctuation-strength-and-roughness
>
>
> 8<-----------------------------------------------------------
>
>
> Sound Quality Algorithms
> Updated Feb 4, 2020
>
>
> Overview
>
> Sound quality, a set of algorithms developed from the science of
> psychoacoustics, is used to define the relationship between the
> physical quantities of sound and the subjective impression as heard by
> the human ear. These algorithms examine physical parameters such as
> sound pressure level, frequency, and modulation depth and correlate
> them to human hearing perception. Sound quality algorithms have
> revolutionized acoustical measurements in the automotive, white goods,
> and other industries by transitioning the focus from simple noise
> emission reduction to a more sophisticated process of increasing sound
> desirability. Sound quality consists of the following algorithms: ISO
> 532B stationary loudness, time-varying loudness, Aures roughness,
> Aures sharpness, Aures tonality, and fluctuation strength. The NI
> Sound and Vibration Measurement Suite provides LabVIEW VIs with which
> you can implement these algorithms.
>
>
> Contents
>
> * Introduction
> * Stationary Loudness
> * Time-Varying Loudness
> * Roughness
> * Sharpness
> * Tonality
> * Fluctuation Strength
> * Conclusion
>
>
> Introduction
>
> For decades, the automotive and aerodynamics industries have used
> acoustical measurements to understand how sounds from turbines,
> motors, and other physical actions affect humans. Until recently, the
> analysis performed on those measurements has been quite simple,
> consisting of sound pressure level analysis, octave analysis, FFT
> analysis, and the application of basic weighting filters. These
> algorithms, while good at revealing the decibel level or frequency
> content of a signal, do not uncover a number of important phenomena
> that determine the desirability of the signal. To move beyond simple
> noise level analysis and perform practical environmental noise
> measurements, sound quality algorithms have been developed to explain
> how sounds are perceived by the human ear.
>
> Sound quality algorithms are the product of research across a spectrum
> of sciences including acoustics, physics, communication engineering,
> mechanical engineering, musicology, marketing, physiology, and
> psychology. These algorithms combine the psychoacoustical, physical,
> and cognitive aspects of sound in order to provide new performance
> metrics to design engineers. An example application of these
> algorithms in the automotive NVH industry is to design an engine with
> a more pleasing sound or a door handle with a more soothing click. The
> sound quality algorithms also are applicable in the production of
> consumer electronics. These algorithms allow an engineer to design a
> better-sounding product, which psychologically increases the chances
> of consumer adoption.
>
> Sound quality consists of the following algorithms: ISO 532B
> stationary loudness, time-varying loudness, Aures roughness, Aures
> sharpness, Aures tonality, and fluctuation strength.
>
>
> Stationary Loudness
>
> Loudness is a term referring to the human perception of sound volume.
> The definition of loudness states that 1 sone, the unit of loudness,
> corresponds to a 1 kHz tone at 40dB. The loudness scale quantifies the
> loudness linearly to the human ear in which a doubling of the
> sone-value maps directly to a doubling in loudness.
>
> Stationary loudness is an algorithm for steady-state noises, or
> signals that do not vary with time. This algorithm measures the 1/3
> octave spectrum, combines the fractional-octave bands into critical
> bands, and then applies spectral masking. This algorithm returns the
> result as the specific loudness versus critical band rate and then
> integrates the specific loudness to measure the total loudness and
> loudness level. This algorithm also is known as ISO 532B loudness or
> Zwicker loudness and is in compliance with ISO 532B, DIN 45631, and
> ISO/R 131.
>
>
> Time-Varying Loudness
>
> Time-varying loudness is an algorithm for calculating the loudness of
> non-steady-state noises, or signals that vary with time. This
> algorithm measures the 1/3 octave spectrum using exponential averaging
> with a 2 ms time constant, combines the fractional-octave bands into
> critical bands, and applies temporal and spectral masking. This
> algorithm then returns the result as the specific loudness versus
> critical band rate, integrates the specific loudness, and applies
> temporal post-masking filters to measure the time-varying loudness.
> This algorithm calculates the time-varying loudness in compliance with
> DIN 45631/A.
>
>
> Roughness
>
> Roughness is another algorithm used to determine the subjective
> judgment of sound quality. Roughness correlates to how noticeable or
> annoying a sound is as heard by the human ear. More specifically,
> roughness is a hearing sensation related to loudness modulations at
> frequencies too high to discern separately, such as modulation
> frequencies greater than 30 Hz.
>
> The roughness algorithm measures the energy in 24 barks, computes and
> filters the envelope of the signal in each band, measures the
> amplitude modulation of each envelope, and then weights the level in
> each band using both the modulation index of that band and a
> frequency-dependent weighting function. The algorithm returns the
> result as the roughness spectrum versus critical band rate and then
> integrates the roughness spectrum to measure the roughness.
>
>
> Sharpness
>
> Sharpness is a hearing sensation related to frequency and independent
> of loudness. Sharpness corresponds to the sensation of a sharp,
> painful, high-frequency sound and is the comparison of the amount of
> high frequency energy to the total energy. The sharpness algorithm
> computes sharpness from the sound pressure signal waveform, the
> 1/3-octave band spectrum calculated over the frequency range 25 Hz to
> 12.5 kHz, or the specific loudness.
>
> This algorithm normalizes the specific loudness spectrum by the total
> loudness and weights the spectrum according to frequency. The
> algorithm returns the frequency-weighted result as the specific
> sharpness versus critical band rate and then integrates the specific
> sharpness to measure the sharpness. Higher frequency components in the
> signal generally result in higher sharpness measurements.
>
>
> Tonality
>
> Tonality is used to determine whether a sound consists mainly of tonal
> components or broadband noise. The algorithm measures the relative
> strength of the tones in a signal compared to the overall signal. For
> each time block, this algorithm first varies the frequency resolution
> according to the frequency selectivity of human hearing, searches the
> spectrum for likely tones, and then compares the loudness of the tones
> to the loudness of the sound.
>
>
> Fluctuation Strength
>
> Fluctuation strength is a hearing sensation related to loudness
> modulations at low frequencies that are discernable individually.
> Fluctuation strength uses a similar method to "roughness versus time"
> analysis except that it focuses specifically on signal variations with
> very low modulation frequencies.
>
> Fluctuation strength measures the energy in 47 overlapping barks,
> computes and filters the envelope of the signal in each band, measures
> the amplitude modulation of each envelope, and weights the level in
> each band using a frequency-dependent weighting function. The
> algorithm returns the result as the fluctuation strength spectrum
> versus critical band rate and then integrates the fluctuation strength
> spectrum to measure the fluctuation strength. The algorithm examines
> modulations between 0 to 30 Hz, with special emphasis on those near 4
> Hz.
>
>
> Conclusion
>
> The Sound and Vibration Measurement Suite provides VIs you can use to
> implement sound quality algorithms. The Sound and Vibration
> Measurement Suite also provides in-depth documentation about each of
> these algorithms. You can download the Sound and Vibration Measurement
> Suite for free as a 7-day trial. You also must install LabVIEW in
> order to use the sound quality algorithms in the Sound and Vibration
> Measurement Suite.
>
> Download and evaluate the Sound and Vibration Measurement Suite
>
>
>
>
> On Sun, Mar 28, 2021 at 3:52 PM cheater cheater
> <cheater00social at gmail.com> wrote:
>>
>> > On Mon, Jan 18, 2021 at 11:49 AM ColinMuirDorward
>> > <colindorward at gmail.com> wrote:
>> > In my 4pole 3320 BPF, the polypropylenes sound slightly better. The
>> > obvious difference is that at lower frequency settings, they go into
>> > self-oscillation more readily than the ceramics. To my biased ear, the
>> > ceramics make some small distortion perhaps, or for some reason add a
>> > slight edge to the sound. I did do a blind test using a 2pole 2164 SVF
>> > and the difference there is more noticeable than in any other filter
>> > I've tested. Here, the polys are a clear win. I want to use words like
>> > "liquid, juicy, lush" for the polys vs "bite, edge, grit" for the
>> > ceramics. However those are too strong words to describe a very subtle
>> > difference. I am waiting to find the right modern mono synth that I can
>> > do a capacitor "upgrade" on and test if it's possible to perceive a
>> > change in the sound in a factory-made unit. I have an uno synth on the
>> > way (was on sale for $135cad?!), perhaps I'll be lucky enough to find
>> > space inside that tiny case for four WIMAs.
>>
>> The sound quality you're talking is "roughness" and is measured in Aspers.
>>
>> Tiny capacitors have a very large voltage gradient across a very short
>> casing. They're probably self-modulating, i.e higher voltage means
>> less capacitance. Essentially self-filter-FM.
>>
>> Look at this article:
>> https://passive-components.eu/dc-and-ac-bias-dependence-of-mlcc-capacitors-including-temperature-dependence/
>>
>> Look at Figure 4. They took ten samples of "1uF 0603 16V X5R parts
>> from Vendor-F" and invariably they lose 40% capacitance at +15V /
>> -15V. So unless you're running your synth at low voltages, you're
>> running into exactly that. I believe there's a filter out there that
>> leverages this, but I forget what it was. There's some filter for sure
>> where the audio was low voltage AC (maybe 100mVpp or less) and the
>> cutoff was high voltage DC (0-x volts). Hell if I know what it was...
>> some EQ maybe? IDK
>>
>> Figure 5 shows capacitors range from -40% to even -80% capacitance at
>> +/-15V depending on make and model.
>>
>> C0G as I understand specifies capacitance retention across temperature
>> ranges. I don't know that they're specified across voltage ranges. A
>> quick look at the first C0G datasheet I could find (from AVX) shows
>> that they don't even specify voltage dependence.
>>
>> So yeah, in this case, physically larger components are just better if
>> you want to stay at +/-15V. Or alternatively go to something like mV
>> range and have a much more linear, tiny, capacitor - but at the cost
>> of EMI adding a bunch of noise. Your choice. Fully-balanced synths
>> anyone? I mean you could probably fit two copies of the same circuit
>> in 0201 in the footprint that you'd otherwise be using for silver mica
>> or red brick wimas.
>>
>> One more option is to add self-filter-fm cancellation to your filter,
>> and have it as part of the tuning or calibration procedure. Probably
>> for the best anyways.
>>
>> Well, that should explain the issue hopefully. Cheers
>
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