sii_ansi_freq

sii_ansi_freq(spectrum, freqs, method, speech_level, threshold=None)

Calculate speech intelligibility index

This function computes SII values for a noise spectrum in dB according to ANSI S3.5 standard.

Parameters:

• spectrum (array_like) – Noise spectrum [dB ref. 2e-5 Pa].

• freqs (array_like) – Frequency axis [Hz] of the spectrum.

• method ({"critical", "equally_critical", "third_octave", "octave"}) – Type of frequency band to be used for the calculation. See § 3.4 of the standard.

• speech_level ({'normal', 'raised', 'loud', 'shout'}) – Speech level to assess, the corresponding speech spectrum defined in the standard is used for calculation.

• threshold (array_like or 'zwicker') – Threshold of hearing [dB ref. 2e-5 Pa] with same size as the chosen method frequency axis, or ‘zwicker’ to use the standard threshold. Default to None sets the threshold to zeros on each frequency band.

Returns:

• sii (numpy.ndarray) – Overall SII value.

• specific_sii (numpy.ndarray) – Specific SII values along the frequency axis.

• freq_axis (numpy.ndarray) – Frequency axis corresponding to the chosen method.

See also

sii_ansi

Speech intelligibility with a time signal as background noise

sii_ansi_level

Speech intelligibility with an overall SPL level as background noise

Warning

Input spectrum must be provided in dB.

Notes

The Speech Intelligibility Index \(SII\) of the signal is computed as the sum of the speech-to-noise ratio \(A\) weighted by an importance function \(I\), over the \(n\) frequency bands.

\[SII=\sum_{i=1}^{n}A_{i}I_{i}\]

The number of frequency bands considered depends on the chosen method:

• “critical”: 21 critical bands corresponding to the Bark scale

• “equally_critical”: 17 equally contributing critical bands

• “third-octave”: 18 third-octave bands

• “octave”: 6 octave bands

References

[1]

ANSI.S3.5:2017. Methods for calculation of the Speech Intelligibility Index. American National Standards Institute, 2017. URL: https://webstore.ansi.org/standards/asa/ansiasas31997r2017.

Examples

>>> from mosqito.sq_metrics import sii_ansi_freq
>>> from mosqito.sound_level_meter.comp_spectrum import comp_spectrum
>>> import matplotlib.pyplot as plt
>>> import numpy as np
>>> fs=48000
>>> d=0.2
>>> dB=60
>>> time = np.arange(0, d, 1/fs)
>>> f = 50
>>> stimulus = np.sin(2 * np.pi * f * time) * np.sin(np.pi * f * time) + np.sin(10 * np.pi * f * time) + np.sin(100 * 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
>>> spec, freqs = comp_spectrum(stimulus, fs, db=True)
>>> SII, SII_spec, freq_axis = sii_ansi_freq(spec, freqs, method='critical', speech_level='normal')
>>> plt.plot(freq_axis, SII_spec)
>>> plt.xlabel("Frequency [Hz]")
>>> plt.ylabel("Specific value ")
>>> plt.title("Speech Intelligibility Index = " + f"{SII:.2f}")

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