sharpness_din_tv

sharpness_din_tv(signal, fs, weighting='din', field_type='free', skip=0)

Compute the sharpness value from a time signal (optionally segmented)

This function computes the sharpness value along time according to different methods.

Parameters:

• signal (array_like) – Input time signal in [Pa], dim (nperseg, nseg)

• fs (float) – Sampling frequency

• weighting ({'din', 'aures', 'bismarck', 'fastl'}) – Weighting function used for the sharpness computation. Default is ‘din’

• field_type ({'free', 'diffuse'}) – Type of soundfield. Default is ‘free’

• skip (float) – Number of second to be cut at the beginning of the analysis to skip the transient effect. Default is 0

Returns:

• S (numpy.array) – Sharpness value in [acum], dim (nseg)

• time_axis (numpy.array) – Time axis in [s]

Warning

The sampling frequency of the signal must be >= 48 kHz to fulfill requirements. If the provided signal doesn’t meet the requirements, it will be resampled.

See also

sharpness_din_from_loudness

Sharpness computation from loudness values

sharpness_din_st

Sharpness computation for a stationary time signal

sharpness_din_perseg

Sharpness computation by time-segment

sharpness_din_freq

Sharpness computation from a sound spectrum

Notes

For each time frame considered, the computation consists of a specific loudness weighting employing a weighting function \(g(z)\):

\[S=0.11\frac{\int_{0}^{24Bark}N'(z)g(z)\textup{dz}}{N}\]

with \(N'\) the specific loudness and \(N\) the global loudness according to Zwicker method for time-varying signals.

The different methods available with the function account for the weighting function applied:

• DIN 45692 : weighting defined in the standard

• Aures

• Bismarck

• Fastl

References

[1]

DIN.45692:2009. Measurement technique for the simulation of the auditory sensation of sharpness. Deutsches Institut fur Normung, 2009. URL: https://www.normadoc.com/english/din-45692-2009-08.html?___from_store=french.

[2]

E.Zwicker and H.Fastl. Psychoacoustics. Springer Berlin, 2007. URL: https://link.springer.com/book/10.1007/978-3-540-68888-4.

[3]

E. von Bismarck. Sharpness as an attribute of the timbre of steady sounds. Acta Acustica, 1974. URL: https://www.ingentaconnect.com/contentone/dav/aaua/1974/00000030/00000003/art00006.

Examples

>>> from mosqito.sq_metrics import sharpness_din_tv
>>> import matplotlib.pyplot as plt
>>> import numpy as np
>>> fs=48000
>>> d=1
>>> dB=60
>>> time = np.arange(0, d, 1/fs)
>>> f = np.linspace(1000,5000, len(time))
>>> stimulus = 0.5 * (1 + np.sin(2 * np.pi * f * time))
>>> rms = np.sqrt(np.mean(np.power(stimulus, 2)))
>>> ampl = 0.00002 * np.power(10, dB / 20) / rms
>>> stimulus = stimulus * ampl
>>> S, time_axis = sharpness_din_tv(stimulus, fs=fs, skip=0.1)
>>> plt.plot(time_axis, S)
>>> plt.xlabel("Time [s]")
>>> plt.ylabel("Sharpness [Acum]")

(Source code, png, hires.png, pdf)