Santiago Pascual1, Joan Serrà2, Antonio Bonafonte1
1Universitat Politècnica de Catalunya, Barcelona, Spain
2Telefónica Research, Barcelona, Spain
This page shows qualitative results for our work on "Exploring Efficient Neural Architectures for Linguistic-Acoustic Mapping in Text-to-Speech". In this work two different pseudo-recurrent mechanisms (QLAD and SALAD) are explored to make acoustic modeling in text-to-speech more efficient whilst trying to maintain the generated speech naturalness.The code of this project is publicly available in GitHub.