Sentence examples for density command from inspiring English sources

These values were converted to a distribution with the density command in R using the default parameters, then the maximum of each distribution was scaled to 1 to make it easier to compare the distributions in Figure  1C.

Unlike other corpora analyzed in this paper, however, the lexical models have a density of commands lower than the automatic models: 40% fewer phrase commands and 14% fewer accent commands.

We can assume that a higher number of free parameters in A-ME + reduces accent command density.

The phrase command density is the lowest for the automatic model, approximately 40% lower than the proposed models.

The root mean square error (RMSE) in semitones (ST) and the average command density per second of the different experiments are shown in Table 2.

Moreover, the accent command density is similar for both alternatives of initialization, but they are lower than that of the prototypes and the automatic approach, and are higher than those obtained from the manual.

Since the models obtained with the proposed method have a lower density of accent commands than the prototypes, the optimization algorithm removes those commands which are considered unnecessary.

The large difference in the density of phrase commands between the two corpora is explained by the fact that, in DB1, we assign one command for each intonation phrase, and in DB2, we assign one command for each pause.

As can be seen, the density of phrase commands remains unchanged.

The tonal model has the lowest density of accent commands, and the lexical model has the highest density.

The lexical approach has an error slightly lower than the automatic model at the expense of a higher density of accent commands.