A Frame Tracking Model for Memory-Enhanced Dialogue Systems
| Autor: | Shikhar Sharma, Layla El Asri, Jeremie Zumer, Hannes Schulz |
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| Rok vydání: | 2017 |
| Předmět: |
060201 languages & linguistics
FOS: Computer and information sciences Computer Science - Computation and Language Computer science Speech recognition Frame (networking) Value (computer science) 06 humanities and the arts 02 engineering and technology Tracking (particle physics) Task (project management) Set (abstract data type) 0602 languages and literature 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing State (computer science) Baseline (configuration management) Computation and Language (cs.CL) Utterance |
| Zdroj: | Rep4NLP@ACL |
| DOI: | 10.48550/arxiv.1706.01690 |
| Popis: | Recently, resources and tasks were proposed to go beyond state tracking in dialogue systems. An example is the frame tracking task, which requires recording multiple frames, one for each user goal set during the dialogue. This allows a user, for instance, to compare items corresponding to different goals. This paper proposes a model which takes as input the list of frames created so far during the dialogue, the current user utterance as well as the dialogue acts, slot types, and slot values associated with this utterance. The model then outputs the frame being referenced by each triple of dialogue act, slot type, and slot value. We show that on the recently published Frames dataset, this model significantly outperforms a previously proposed rule-based baseline. In addition, we propose an extensive analysis of the frame tracking task by dividing it into sub-tasks and assessing their difficulty with respect to our model. |
| Databáze: | OpenAIRE |
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