plot.cond: Plot several DET plots from a single trial list, analyzed per...
In davidavdav/sretools.R: Compute error metrics and make DET plots for NIST-like Speaker Recognition Evaluations

Description Usage Arguments Details Value Author(s) References See Also Examples

This function plots DET curves for all conditions in a multi-condition trial set, such as NIST SRE-2008. An overall DET curve, equalizing trial counts, is also plotted.

1	plot.cond(x, cond, nr = 1, equalize = T, ...)

`x`	A data.frame of class `sre`/
`cond`	A list of factors specifying the conditions
`nr`	The number (color) of the first line.
`equalize`	Do we equalize the overall DET curve?
`...`	further parameters for `plot.det()`

For each condition determined by the list of factors, a separate DET will be plotted in a new color. The overall condition is plotterd in black, as a last curve so that it will be “on top of” the other curves. You may find yourself soon to be running out of sensible colors.

It is possible to specify equalize=FALSE purely for demonstration purposes, we don't believe this makes very much sense.

A table with a summary of the main detection performance metrics for each condition, and averaged over all conditions (but equalized for trial counts).

David van Leeuwen

David A. van Leeuwen, “Overal performance metrics for multi-condition Speaker Recognition Evaluations,” Proc. Interspeech, Brighton, September 2009, pp 908–911.

cond.table, plot.det

## load data
data(tno.2008)
## plot for all sensible conditions
plot.cond(tno.2008, list(mtype, ttype, tmic))
## another eval
data(ru.2009)
setDCF("evalita")
## we can plot fol all train/test conditions in one go...
plot.cond(ru.2009, list(mcond, tcond))
## or look at gender effect, or channel
x <- subset(ru.2009, mcond=="TC6" & tcond=="TS2")
plot.cond(x, gender)
plot.cond(x, channel)