At the point where distinct groups within the data are forced to be joined, costs should increase significantly in comparison to neighboured values and thereby give a hint at a suitable number of clusters to be built from the given data.
Join cost computation: Join cost indicates how well the two adjacently selected units join together.
To calculate the join cost between two segments, both auditory and visual properties are used.
If the phone at the join position is voiceless, this pitch join cost is set to zero.
We describe target cost and join cost implementation for such a system and describe the outcome of building voices with a number of different sized datasets.
Finally, the derivative join cost DVC is calculated in the same manner as VC using the derivatives of the PC trajectories.
The visual join cost calculation was based on the pixel-to-pixel color differences in the boundaries of the segments to be concatenated.
The relational algebra, query trees, and join cost function are used to examine the effect on the performance of relational systems.
In designing a relational schema, we often consider that an attribute of a table is replicated into other table to reduce the join cost.
For each concatenation, the exact join position is determined by examining the audio tracks and selecting the pair of pitch mark instants that minimizes the auditory join cost for this particular join [27].
The cost of selecting a particular audiovisual unit includes target cost functions that indicate how well this segment matches the target speech, and join cost functions that indicate how well two consecutive segments can be concatenated without creating disturbing artifacts.
