@inproceedings{ma2015knowledge,
author = {Ma, Yi and Crook, Paul A. and Sarikaya, Ruhi and Fosler-Lussier, Eric},
title = {Knowledge Graph Inference for Spoken Dialog Systems},
booktitle = {Proceedings of 40th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2015},
year = {2015},
month = {April},
abstract = {We propose Inference Knowledge Graph, a novel approach of remapping existing, large scale, semantic knowledge graphs into Markov Random Fields in order to create user goal tracking models that could form part of a spoken dialog system. Since semantic knowledge graphs include both entities and their attributes, the proposed method merges the semantic dialog-state-tracking of attributes and the database lookup of entities that fulfill users’ requests into one single unified step. Using a large semantic graph that contains all businesses in Bellevue, WA, extracted from Microsoft Satori, we demonstrate that the proposed approach can return significantly more relevant entities to the user than a baseline system using database lookup.},
publisher = {IEEE - Institute of Electrical and Electronics Engineers},
url = {http://approjects.co.za/?big=en-us/research/publication/knowledge-graph-inference-for-spoken-dialog-systems/},
edition = {Proceedings of 40th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2015},
}