During training, we apply some noise to a(x, v src ) by randomly altering each attribute marker in it independently with probability 0.1.
we replace an attribute marker with another randomly selected attribute marker of the same attribute and word-level edit distance 1 if such a noising marker exists, e.g., "was very rude" to "very rude", which produces a (x, v src ).