Abstract

The quality of corpus-based text-to-speech systems depends on the accuracy of the unit selection process, which in turn relies on the cost function definition. This function should map the user perceptual preference when selecting synthesis units, which is a very difficult task. This paper continues our previous work on fusing the human judgements with the cost function by means of interactive weight tuning. The application of active interactive genetics algorithms mitigates user fatigue by improving user consistency. As a result, the obtained weights generate more natural synthetic speech when compared to previous objective and subjective proposals.

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