Abstract:
Following the successful findings of high
correlations between speech and color such as F0 and
Value, Loudness and Saturation and Spectrum and
Hue, we analyzed the correlations between voice
source characteristics and the image parameters
showing textural differences in this paper for better
scientific understanding of their correlations and
effective use in visualization of speech information.
Through sentiment association experiments, we could
have observed high positive correlations between H1*-
H2* (amplitude difference between first and second
harmonics corrected for vocal tract effects), H1-A1
(amplitude difference between first harmonic and first
formant) and Contrast, high negative correlations
between H1*-H2*, H1-A1, H1-A2, H1-A3, Harmonicto-
Noise Ratio (HNR) in 0 to 3500Hz frequency band
and Variance, Prominence and negative correlations
between H1*-A3*, HNR in 0 to 500 Hz and
Prominence. These results show the possibility of
direct visualization of speech characteristics which
cannot be effectively carried out by conventional
mapping using discrete language expressions.
