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

23 citations · 25 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2024★ 23 cited

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

Mateusz Łajszczak, Guillermo Cámbara, Yang Li +16

We introduce a text-to-speech (TTS) model called BASE TTS, which stands for ig daptive treamable TTS with mergent abilities. BASE TT…

cs.LG2023★ 2 cited

SMAClite: A Lightweight Environment for Multi-Agent Reinforcement Learning

Adam Michalski, Filippos Christianos, Stefano V. Albrecht

There is a lack of standard benchmarks for Multi-Agent Reinforcement Learning (MARL) algorithms. The Starcraft Multi-Agent Challenge (SMAC) has been widely used in MARL research, b…