13. 12. 2022
David Lukeš
[T]he function of language is not so much to convey knowledge (according to the common phrase) from one mind to another, as to bring two minds into the same train of thinking; and to confine them as nearly as possible, to the same track.
– Dugald Stewart (1810), Philosophical Essays
Arnulf Depperman (spoluautor transkripčních pravidel GAT-2) má ve sborníku Prosody in interaction (2010) příspěvek nazvaný “Future prospects of research on prosody: The need for publicly available corpora”
Suprasegmentální variace…
… ve frekvenční doméně (intonace; akusticky F0 neboli základní frekvence)
… v temporální doméně (tempo, rytmus)
Rozpětí intonace u rozhlasových mluvčích (10.–90. percentil) dle Volína et al. (2015), “Speech melody properties in English, Czech and Czech English: Reference and interference”:
| pohlaví ↓ zdroj → | čtená čeština | čtená angličtina |
|---|---|---|
| ženy | 5.2 | 7.1 |
| muži | 6.1 | 8.1 |
Též nižší medián.
Fixní přízvuk, bez nápadných akustických korelátů (Skarnitzl 2018, “Fonetická realizace slovního přízvuku u delších slov v češtině”)
U nás:
Mezinárodně:
protožeprotoʒɛ → protože_protoʒɛprotožebʒɛ → protože_bʒɛ
| kind | gender | proportion of glissandos |
|---|---|---|
| dialogue | female | 0.0387 |
| male | 0.0401 | |
| monologue | female | 0.0454 |
| male | 0.0488 |
OLS Regression Results
==============================================================================
Dep. Variable: range R-squared: 0.003
Model: OLS Adj. R-squared: 0.003
No. Observations: 275358 F-statistic: 316.4
Covariance Type: nonrobust Prob (F-statistic): 4.09e-205
====================================================================================================
coef std err t P>|t| [0.025 0.975]
----------------------------------------------------------------------------------------------------
Intercept 5.2111 0.015 341.629 0.000 5.181 5.241
kind[T.monologue] -0.6169 0.024 -25.926 0.000 -0.664 -0.570
gender[T.male] -0.4560 0.022 -20.904 0.000 -0.499 -0.413
kind[T.monologue]:gender[T.male] 0.9367 0.031 30.623 0.000 0.877 0.997
====================================================================================================
Porovnání s již zmiňovanými daty od Volína et al. (2015)
| pohlaví ↓ zdroj → | český dialog | český monolog | čeština čtená | angličtina čtená |
|---|---|---|---|---|
| ženy | 5.21 | 4.59 | 5.2 | 7.1 |
| muži | 4.76 | 5.07 | 6.1 | 8.1 |
Mixed Linear Model Regression Results
==============================================================================
Model: MixedLM Dependent Variable: range
No. Observations: 119693 Method: REML
No. Groups: 926 Scale: 14.4776
Min. group size: 1 Log-Likelihood: -330769.0909
Max. group size: 1147 Converged: Yes
Mean group size: 129.3
------------------------------------------------------------------------------
Coef. Std.Err. z P>|z| [0.025 0.975]
------------------------------------------------------------------------------
Intercept 4.841 0.169 28.717 0.000 4.511 5.172
gender[T.male] -0.902 0.195 -4.630 0.000 -1.285 -0.520
reg_childhood[T.pohraničí moravské] 0.242 0.181 1.337 0.181 -0.113 0.597
reg_childhood[T.pohraničí české] 0.318 0.172 1.852 0.064 -0.019 0.654
reg_childhood[T.severovýchodočeská] 0.471 0.177 2.656 0.008 0.123 0.818
reg_childhood[T.slezská] 0.405 0.167 2.421 0.015 0.077 0.733
reg_childhood[T.středomoravská] 0.189 0.162 1.165 0.244 -0.129 0.507
reg_childhood[T.středočeská] 0.187 0.160 1.173 0.241 -0.126 0.501
reg_childhood[T.východomoravská] 0.354 0.171 2.069 0.039 0.019 0.690
reg_childhood[T.západočeská] 0.207 0.169 1.221 0.222 -0.125 0.538
reg_childhood[T.česko-moravská] 0.390 0.173 2.251 0.024 0.050 0.729
age 0.002 0.003 0.533 0.594 -0.004 0.008
gender[T.male]:age 0.014 0.005 3.015 0.003 0.005 0.023
Group Var 1.177 0.017
==============================================================================