  This article evaluates a first experience of generating artificial children's
voices with a Costa Rican accent, using the technique of statistical parametric
speech synthesis based on Hidden Markov Models. The process of recording the
voice samples used for learning the models, the fundamentals of the technique
used and the subjective evaluation of the results through the perception of a
group of people is described. The results show that the intelligibility of the
results, evaluated in isolated words, is lower than the voices recorded by the
group of participating children. Similarly, the detection of the age and gender
of the speaking person is significantly affected in artificial voices, relative
to recordings of natural voices. These results show the need to obtain larger
amounts of data, in addition to becoming a numerical reference for future
developments resulting from new data or from processes to improve results in
the same technique.
