Spoken Dialogue Systems
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Hierarchical Multi-Task Natural Language Understanding for Cross-domain Conversational AI: HERMIT NLU
We present a new neural architecture for wide-coverage Natural Language Understanding in Spoken Dialogue Systems.
Findings of the E2E NLG Challenge
WS 2018
• UFAL-DSG/tgen
• 
This paper summarises the experimental setup and results of the first shared task on end-to-end (E2E) natural language generation (NLG) in spoken dialogue systems.
#3 best model for
Data-to-Text Generation
on E2E NLG Challenge
A Context-aware Natural Language Generator for Dialogue Systems
• UFAL-DSG/tgen
•
We present a novel natural language generation system for spoken dialogue systems capable of entraining (adapting) to users' way of speaking, providing contextually appropriate responses.
Slot-Gated Modeling for Joint Slot Filling and Intent Prediction
NAACL 2018
• MiuLab/SlotGated-SLU
•
Attention-based recurrent neural network models for joint intent detection and slot filling have achieved the state-of-the-art performance, while they have independent attention weights.
INTENT DETECTION SLOT FILLING SPOKEN DIALOGUE SYSTEMS SPOKEN LANGUAGE UNDERSTANDING
Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems
EMNLP 2015
• andy194673/nlg-sclstm-multiwoz
• 
Natural language generation (NLG) is a critical component of spoken dialogue and it has a significant impact both on usability and perceived quality.
How Time Matters: Learning Time-Decay Attention for Contextual Spoken Language Understanding in Dialogues
NAACL 2018 • MiuLab/Time-Decay-SLU
Spoken language understanding (SLU) is an essential component in conversational systems.
DIALOGUE STATE TRACKING IMAGE CAPTIONING MACHINE TRANSLATION SLOT FILLING SPOKEN DIALOGUE SYSTEMS SPOKEN LANGUAGE UNDERSTANDING
Variational Cross-domain Natural Language Generation for Spoken Dialogue Systems
WS 2018
• andy194673/nlg-scvae
•
Cross-domain natural language generation (NLG) is still a difficult task within spoken dialogue modelling.