Дата: 8-07-2022, 03:19
Experiments on two domains of the MultiDoGO dataset reveal challenges of constraint violation detection and sets the stage for future work and enhancements. The outcomes from the empirical work show that the new rating mechanism proposed will likely be more effective than the previous one in a number of points. Extensive experiments and analyses on the lightweight models show that our proposed strategies achieve significantly higher scores and considerably improve the robustness of both intent detection and slot filling. Data-Efficient Paraphrase Generation to Bootstrap Intent Classification and Slot Labeling for brand spanking new Features in Task-Oriented Dialog Systems Shailza Jolly writer Tobias Falke author Caglar Tirkaz writer Daniil Sorokin writer 2020-dec text Proceedings of the 28th International Conference on Computational Linguistics: Industry Track International Committee on Computational Linguistics Online convention publication Recent progress via advanced neural models pushed the efficiency of process-oriented dialog techniques to almost excellent accuracy on current benchmark datasets for intent classification and slot labeling.