Pre-Trained and Attention-Based Neural Networks for Building Noetic Task-Oriented Dialogue Systems
About
The NOESIS II challenge, as the Track 2 of the 8th Dialogue System Technology Challenges (DSTC 8), is the extension of DSTC 7. This track incorporates new elements that are vital for the creation of a deployed task-oriented dialogue system. This paper describes our systems that are evaluated on all subtasks under this challenge. We study the problem of employing pre-trained attention-based network for multi-turn dialogue systems. Meanwhile, several adaptation methods are proposed to adapt the pre-trained language models for multi-turn dialogue systems, in order to keep the intrinsic property of dialogue systems. In the released evaluation results of Track 2 of DSTC 8, our proposed models ranked fourth in subtask 1, third in subtask 2, and first in subtask 3 and subtask 4 respectively.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Dialogue Thread Reconstruction (Subtask 4) | Ubuntu Track 2 DSTC 8 (test) | Precision44.3 | 1 | |
| Response Selection (Subtask 1) | Ubuntu Track 2 DSTC 8 (test) | Recall@164.9 | 1 | |
| Response Selection (Subtask 1) | Advising Track 2 DSTC 8 (test) | Recall@122.4 | 1 | |
| Response Selection with Multiple Correct Responses (Subtask 3) | Advising Track 2 hidden DSTC 8 (test) | Accuracy0.802 | 1 | |
| Response Selection with No Correct Response (Subtask 2) | Ubuntu Track 2 DSTC 8 (test) | Recall@150.6 | 1 |