  We estimate the $n$-gram entropies of natural language texts in word-length
representation and find that these are sensitive to text language and genre. We
attribute this sensitivity to changes in the probability distribution of the
lengths of single words and emphasize the crucial role of the uniformity of
probabilities of having words with length between five and ten. Furthermore,
comparison with the entropies of shuffled data reveals the impact of word
length correlations on the estimated $n$-gram entropies.
