Generacion de voces artificiales infantiles en castellano con acento costarricense
This addresses the problem of creating synthetic children's voices for Spanish with regional accents, but it is incremental as it applies an existing method to new data.
The researchers tackled generating artificial children's voices with a Costa Rican accent using statistical parametric speech synthesis based on Hidden Markov Models, finding that the intelligibility of isolated words was lower than natural recordings and age/gender detection was significantly worse.
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.