no code implementations • 6 Nov 2016 • Yehoshua Dissen, Joseph Keshet, Jacob Goldberger, Cynthia Clopper
We then freeze the parameters of the trained network and use several different datasets to train an adaptation layer that makes the obtained network universal in the sense that it works well for a variety of speakers and speech domains with very different characteristics.
1 code implementation • 26 Oct 2016 • Yossi Adi, Joseph Keshet, Emily Cibelli, Erin Gustafson, Cynthia Clopper, Matthew Goldrick
Manually-annotated data were used to train a model that takes as input an arbitrary length segment of the acoustic signal containing a single vowel that is preceded and followed by consonants and outputs the duration of the vowel.