Adam Polyak

Adam is a research engineer at Facebook AI Research (FAIR), focusing on deep learning, cross domain image generation, audio generation, and voice conversion. He has a B.S. in computer science and mathematics from Bar-Ilan University, and an M.S. in computer science from Tel Aviv University.

Adam's Publications



A Universal Music Translation Network

We present a method for translating music across musical instruments and styles. This method is based on unsupervised training of a multi-domain wavenet autoencoder, with a shared encoder and a domain-independent latent space that is trained…

Noam Mor, Lior Wolf, Adam Polyak, Yaniv Taigman



Attention-Based WaveNet Autoencoder for Universal Voice Conversion

We present a method for converting any voice to a target voice. The method is based on a WaveNet autoencoder, with the addition of a novel attention component that supports the modification of timing between the input and the output samples.…

Adam Polyak, Lior Wolf



Unsupervised Generation of Free-Form and Parameterized Avatars

We study two problems involving the task of mapping images between different domains. The first problem, transfers an image in one domain to an analog image in another domain. The second problem, extends the previous one by mapping an input…

Adam Polyak, Yaniv Taigman, Lior Wolf