Personalized News Event Retrieval for Small Talk in Social Dialog Systems

Konferenz: Speech Communication - 12. ITG-Fachtagung Sprachkommunikation
05.10.2016 - 07.10.2016 in Paderborn, Deutschland

Tagungsband: ITG-Fb. 267: Speech Communication

Seiten: 5Sprache: EnglischTyp: PDF

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Autoren:
Bechberger, Lucas (Interactive Systems Lab (ISL), Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany & Human Language Technology (HLT), Fondazione Bruno Kessler (FBK), Trento, Italy)
Schmidt, Maria; Waibel, Alex (Interactive Systems Lab (ISL), Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)
Federico, Marcello (Human Language Technology (HLT), Fondazione Bruno Kessler (FBK), Trento, Italy)

Inhalt:
This paper presents the NewsTeller system which retrieves a news event based on a user query and the user’s general interests. It can be used by a social dialog system to initiate news-related small talk. The NewsTeller system is implemented as a pipeline with four stages: After collecting a large set of potentially relevant news events, a classifier is used to filter out malformed events. The remaining events are then ranked according to a relevance value predicted by a regressor. In a final step, a short summary of the highest-ranked event is generated and returned to the user. Both the classifier and the regressor were evaluated on hand-labeled data sets. In addition to this, a user study was conducted to further validate the system. Evaluation results indicate that the proposed approach performs significantly better than a random baseline.