[FEATURE] add loudness_match and compare_loudness to pytta.psychoacoustics - #94

tonality_aures1985(signal, field='free', time_skip=0.0) gives the
tonality K(t) and its mean in tonality units: the tonal components of
Terhardt, Stoll and Seewann (1982) in Hann frames of 160 ms, weighted by
bandwidth, frequency and level excess, and the loudness ratio WGr of the
signal without and with them (Aures 1985).

It is written from the two papers. SQAT's Tonality_Aures1985 is GPL-3.0
and served only as the test oracle. The private helper of the Terhardt
excitation is shared with the roughness port, whose parity with SQAT is
unchanged.

Tests check the unit (a 1 kHz tone at 60 dB is 1 t.u.), the level excess
weighting against its formula, parity with SQAT on golden data from
tests/golden/make_tonality_sqat.m (tones within 3.4e-5 t.u., a tone in
noise within 0.012 t.u.) and the rejection of invalid input.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>

…oacoustics

fluctuation_strength_osses2016(signal, time_skip=0.0) gives FS(t) every
0.2 s over frames of 2 s, the specific fluctuation strength over 47
half-Bark channels and the mean FSmean, in vacil, after Osses, Garcia
and Kohlrausch (2016): the roughness model of Daniel and Weber with
frames of 2 s, a modulation weighting H(fmod), the generalised
modulation depth compressed above 0.7 and FS = C_FS sum (m*)^1.7
|k k|^1.7 g(z).

It is written from the paper. SQAT's FluctuationStrength_Osses2016 and
its H(fmod) data are GPL-3.0 and served only as the test oracle. The
paper does not give the filter type of H(fmod), so its cut-offs (1.75
and 13.5 Hz) were fitted to the AM tones of the paper's Table 1. The
result differs from SQAT, as the docstring states: within 1 % for AM
tones at 4 Hz, 4 % at 16 Hz, 14 % above for an FM tone, and about half
of SQAT's value for AM at 1 Hz.

Tests check the unit (1 vacil for the reference AM tone), the AM tones
of Table 1 (rms deviation 0.09 vacil), the comparison with SQAT on
golden data from tests/golden/make_fluctuation_sqat.m with the
tolerances above, and the rejection of invalid input.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>

…to pytta.psychoacoustics

sharpness_din45692 gets weighting='din', 'aures' or 'bismarck': the
weightings of Aures (which depends on the total loudness) and of von
Bismarck, Formulae (B.1) and (B.2) of DIN 45692, Annex B, with the same
k = 0.11, as SQAT and the MATLAB acousticSharpness that the ITA-Toolbox
calls offer.

loudness_level and loudness_from_level convert between sone and phon by
ISO 532-1, Formulae (1) to (3), as ita_sone2phon. critical_band gives
the critical band rate and bandwidth of Zwicker and Terhardt (1980),
with the band edges, as ita_freq2cb (which squares the arctangent of the
second term of the rate; the docstring says so).

Tests check that von Bismarck equals DIN when no loudness lies above
15 Bark, parity of the three weightings with SQAT on golden data from
tests/golden/make_sharpness_weights_sqat.m (within 3.6e-15 acum), the
loudness level formulae and their inverse, and the critical band at
1 kHz and against the table of Zwicker.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>

…stics

loudness_match(reference, signal) gives the gain in dB that gives
signal the loudness of reference, N or (time_varying=True) N5, as
ita_loudness_adjustment of the ITA-Toolbox. The loudness grows with the
gain, so the gain is bracketed in steps of 10 dB, as there, and solved
to 0.001 dB.

compare_loudness(signal_a, signal_b) gives the ratio of the
time-varying specific loudness of two signals, folded to 1 or more, as
ita_loudness_compare_rir.

Tests check that a copy 10 dB down needs +10 dB, that the gain gives a
different sound the loudness of the reference within 1 %, and that the
comparison is 1 for identical sounds and symmetric.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>