Generating Diverse Translation by Manipulating Multi-Head Attention
Table 10: Conversation Response Generation experiment results on STC dataset.
['[EMPTY]', 'BLEU \\uparrow', 'Rel \\uparrow', 'Flu \\uparrow', 'Inf \\uparrow', 'Div \\downarrow']
On one hand, our method achieves significant improvement in generation diversity. On the other hand, the quality including relevance, fluency and informativeness all rise to some degree. After looking into cases, we suppose it is because original Seq2Seq model tends to generate safe outputs like “I don’t know” or simply copying from the source side. In contrast, our method brings in randomness, reaching broader generation space.