Search Results for author: Adam Michalski

Found 2 papers, 1 papers with code

BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data

no code implementations12 Feb 2024 Mateusz Łajszczak, Guillermo Cámbara, Yang Li, Fatih Beyhan, Arent van Korlaar, Fan Yang, Arnaud Joly, Álvaro Martín-Cortinas, Ammar Abbas, Adam Michalski, Alexis Moinet, Sri Karlapati, Ewa Muszyńska, Haohan Guo, Bartosz Putrycz, Soledad López Gambino, Kayeon Yoo, Elena Sokolova, Thomas Drugman

Echoing the widely-reported "emergent abilities" of large language models when trained on increasing volume of data, we show that BASE TTS variants built with 10K+ hours and 500M+ parameters begin to demonstrate natural prosody on textually complex sentences.

Disentanglement

SMAClite: A Lightweight Environment for Multi-Agent Reinforcement Learning

1 code implementation9 May 2023 Adam Michalski, Filippos Christianos, Stefano V. Albrecht

The Starcraft Multi-Agent Challenge (SMAC) has been widely used in MARL research, but is built on top of a heavy, closed-source computer game, StarCraft II.

reinforcement-learning Reinforcement Learning (RL) +3

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