8a. Introduction to similarity measurements
The similarity measurements implement the same feature-based metrics of Euclidean
distances used for the cluster analysis, except that here we do not look across thousands
of syllables, but rather at the time course of feature values across two specific sounds.
Similarity measurements should not be used for comparing simple sounds (such as two
tones), in such cases, differences across mean and range of features is preferred.
Similarity measurements are necessary for comparing two complex sounds, e.g., a pair of
songs or several pairs of complex syllables. Although SA+ segments sounds to syllables,
this segmentation is not used as a unit of similarity analysis, that is, we compare
everything to everything in the two sounds regardless of syllable structure.
Limitation: Similarity measures must be tuned to each species. The current version is
tuned to zebra finches. SA+ makes it very easy to set and save feature scales to other
species. Setting the feature scale for a new species is easy. First, set all the sliders to the
new position and then click 'save new scale' and type the new species name. You can
then browse between the settings by clicking the up and down arrowheads. Note that
SA+ will always start with the default setting (zebra finch) and you should remember to
set it each time to the appropriate species.
The aim of analysis is to address three issues:
· Assessing the likelihood that two sounds are related to each other.
· Quantifying the accuracy of the vocal match (assuming that sounds are
related).
· Accounting for the temporal order (syntax) of sounds when scoring
similarity.
Similarity measurements in SA+ are quite different than those used in previous versions
of Sound Analysis:
· Similarity measurements are more accurate and more transparent to
the user.
· Both symmetric and asymmetric similarity measurements methods are
implemented.
· Partial similarity scores are shown for each syllable.
· Users can open two long recording sessions (of a few minutes each)
and perform partial. similarities much more efficiently without
draining memory.
· New features include amplitude modulation (AM) and goodness of
pitch. We eliminated the spectral continuity feature
· Automated batching provides a link between cluster analysis and
similarity measurements, allowing a fully automated measurement of
thousands of sounds, which are automatically opened, outlined and
scored.
· The memory management scheme has been altered to reduce memory
allocation error and optimize the section detection.
Created using Helpmatic Pro HTML