Class

This week’s class will develop sequence-to-sequence models by improving on the simple DNN from the previous module. After covering the necessary neural building blocks, we will do two case studies based on the Essential readings. Make sure you have read both papers beforehand, and bring copies with you to class.

Download the slides for the class on 2026-03-03

The slides are now the post-class version. The case study on FastPitch was not covered in class, so it is set as homework. We will quickly go over this in the next class.

You need to search for example model output on your own, as part of exploring the literature. You should have found the official Google Tacotron 2 samples page. You can listen to samples comparing FastPitch and Tacotron at https://fastpitch.github.io/ For the state-of-the-art models coming up in the remainder of the course, first read the paper, then search for samples to listen to (sometimes the paper will have a link to a demo page).