  Speech provides a natural way for human-computer interaction. In particular,
speech synthesis systems are popular in different applications, such as
personal assistants, GPS applications, screen readers and accessibility tools.
However, not all languages are on the same level when in terms of resources and
systems for speech synthesis. This work consists of creating publicly available
resources for Brazilian Portuguese in the form of a novel dataset along with
deep learning models for end-to-end speech synthesis. Such dataset has 10.5
hours from a single speaker, from which a Tacotron 2 model with the RTISI-LA
vocoder presented the best performance, achieving a 4.03 MOS value. The
obtained results are comparable to related works covering English language and
the state-of-the-art in Portuguese.
