The first experiment consisted of generating parameter prediction
models from the automatically labelled Tilt events. An optimised
prediction model was created for each parameter (start F_{0},
amplitude, duration, tilt, peak position) of each event type. That is,
not all features were used in each model and hand experimentation was
used to find an optimal set of features. The CART method can deal
with a certain amount of noise in the input features but will be
misled by too much noise (even with cross validation). Tables
1 - 3 show the RMSE and correlation of each
of the twelve optimised models.

**Table 1:** RMSE and Correlation of accent models

**Table 2:** RMSE and Correlation of boundary models

The generated F_{0} is generally similar to the smoothed original. As
an overall measure of accuracy for the 28 test utterance, we
get an average RMSE of 32.5Hz and correlation of 0.60.

**Table 3:** RMSE and Correlation of c and sil models

Tue Jul 1 11:51:11 BST 1997