Chapter 11. Generating Graphics with Splus

Table of Contents

One dimensional plots
Ellipse plotting
Plotting signal files for a single utterance
Plotting segment data: Multiple plots
Plotting segment data: superimposed plots

The following is a description of some of the plotting functions which have been specifically written in Emu for analysing speech data. All of these plots are built on S-plus graphical primitives. See e.g. the S-plus plotting functions plot, barplot, hist.

One dimensional plots

Histogram plots

The Emu function hplot can be used to plot histograms of a single acoustic parameter for multiple types of segments. It takes two obligatory arguments: a vector of values, and a parallel label vector to relate the vector to different labels.

In this example, a histogram is plotted of the F2 values at the segment midpoint of [i:] (e.g. heed) [o:] (hoard) and [A] (had) vowels from the database.

segs <- emu.query("demo", "*", "Phonetic=i:|o:|A") 
vals <- emu.track(segs, "fm", cut=0.5)
hplot(vals[,2], label(segs), xlab="F2 Frequency (Hz)")


Fitting a normal curve to data

The function nplot can be used to fit a normal curve to single parameter data. Like hplot, it takes two required arguments: a vector of parameter values, and a parallel label file.

This example uses the same data as in the nplot example above:

nplot(vals[,2], l.segs, xlab="F2 Frequency (Hz)")


Figure 11.1, “Examples of hplot (upper) and nplot (lower).” shows the results of these two examples.

Figure 11.1. Examples of hplot (upper) and nplot (lower).

Examples of hplot (upper) and nplot (lower).

Note that if the second argument, the parallel vector of labels, is omitted, then nplot assumed all tokens to belong to a single class, and one normal curve for all tokens is plotted.