TITLE: AutoChart: A Dataset for Chart-to-Text Generation Task 

ABSTRACT: The analytical description of charts is an exciting and important research
area with many applications in academia and industry. Yet, this challenging
task has received limited attention from the computational linguistics research
community. This paper proposes \textsf{AutoChart}, a large dataset for the
analytical description of charts, which aims to encourage more research into
this important area. Specifically, we offer a novel framework that generates
the charts and their analytical description automatically. We conducted
extensive human and machine evaluations on the generated charts and
descriptions and demonstrate that the generated texts are informative,
coherent, and relevant to the corresponding charts.
The analytical description of charts is an exciting and important research
area with many applications in academia and industry. Yet, this challenging
task has received limited attention from the computational linguistics research
community. This paper proposes \textsf{AutoChart}, a large dataset for the
analytical description of charts, which aims to encourage more research into
this important area. Specifically, we offer a novel framework that generates
the charts and their analytical description automatically. We conducted
extensive human and machine evaluations on the generated charts and
descriptions and demonstrate that the generated texts are informative,
coherent, and relevant to the corresponding charts.
AutoChart: A Dataset for Chart-to-Text Generation Task
http://arxiv.org/abs/2108.06897v1