The class ColorationKS implements the prediction of the perceived change in
timbre of an auditory event compared to a reference. The reference is nothing
fixed, but can be learned and is stored inside the blackboard memory. At the
moment the learning is implemented in a very low level fashion: the first signal
the Blackboard system is confronted with is learned as the reference and all later
signals are compared to that reference. The colorationHypotheses is then a
value between 0 and 1 – whereas it is not hard limited and can be larger than 1
for some conditions. The actual value is calculated using the naturalness model
from [MooreTan2004] which compares the weighted excitation patterns of the
reference and the test stimulus.
| binds to |
AuditoryFrontEndKS.KsFiredEvent |
| reads data category |
colorationReference |
| writes data category |
colorationHypotheses or colorationReference |
| triggers event |
KsFiredEvent |
As the current implementation of GmmLocationKS and DnnLocationKS are
not able to predict the localisation reliable under difficult conditions, we
introduced a different location knowledge source as an intermediate solution.
This ItdLocationKS is optimised for the prediction of predicting the
perceived direction of a sound source created by a spatial audio system. It uses
only ITD cues under 1400 Hz and utilises a lookup table to match those values
to the corresponding angles. This implies that the knowledge source is not able
to distinguish between front and back. Beside the lookup table it uses also an
outlier detection in the process of integrating the perceived angles over the
different frequency channels as suggested in [Wierstorf2014]. The output of the
knowledge source is a sourcesAzimuthsDistributionHypotheses identical to the
output of the GmmLocationKS or DnnLocationKS.
| binds to |
AuditoryFrontEndKS.KsFiredEvent |
| writes data category |
sourcesAzimuthsDistributionHypotheses |
| triggers event |
KsFiredEvent |
| [MooreTan2004] | Moore, B. C. J., & Tan, C. (2004) Development and Validation of a Method for
Predicting the Perceived Naturalness of Sounds Subjected to Spectral
Distortion. JAES, 52(9), 900–14. |