Multi-Turn Beam Search for Neural Dialogue Modeling
Table 4: Human evaluation scores with respect to different utterance-level inference algorithms, using the egocentric partner model. Beam: vanilla beam search. Iterbeam: iterative beam search (Kulikov et al., 2018).
['Steps', '0', '1', '2', '4', '8']
How important is the partner model? On the other hand, the egocentric and transparent models generate increasingly better responses with more lookahead steps, until performance degrades with 8 lookahead steps. We do not observe any significant difference between the two—performing more lookahead steps with iterative beam search leads to better dialogue responses as well as with vanilla beam search. This shows that our multi-turn approach is robust to the choice of the search algorithm used at the utterance level.