Before revision: Filtering noisy training data is one of the key approaches to improving the quality of neural network-based language generation. The dialogue research community especially suffers from a lack of less-noisy and sufficiently large data .
After revision: Large-scale dialogue datasets have recently become available for training neural dialogue agents. However, these datasets have been reported to contain a non-negligible number of unacceptable utterance pairs .