![](bga.png)
the proposed framework with a generative adversarial
network for synthesizing high quality sentence candi-
dates.
ACKNOWLEDGEMENTS
The authors would like to thank the Ministry of Ed-
ucation, Culture, Sports, Science and Technology
(MEXT) of Japan for providing the Japanese Gov-
ernment (Monbukagakusho) Scholarship under which
this work was carried out. This work was also sup-
ported in part by the Asian Office of Aerospace Re-
search and Development (AOARD), Air Forced Of-
fice of Scientific Research (Grant no. FA2386-19-1-
4041).
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