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Intent Detection

17 papers with code · Natural Language Processing

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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

Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling

6 Sep 2016DSKSD/RNN-for-Joint-NLU

Attention-based encoder-decoder neural network models have recently shown promising results in machine translation and speech recognition.

INTENT CLASSIFICATION INTENT DETECTION SLOT FILLING

Efficient Intent Detection with Dual Sentence Encoders

10 Mar 2020PolyAI-LDN/polyai-models

Building conversational systems in new domains and with added functionality requires resource-efficient models that work under low-data regimes (i. e., in few-shot setups).

INTENT DETECTION

Joint Slot Filling and Intent Detection via Capsule Neural Networks

ACL 2019 czhang99/Capsule-NLU

Being able to recognize words as slots and detect the intent of an utterance has been a keen issue in natural language understanding.

INTENT DETECTION NATURAL LANGUAGE UNDERSTANDING SLOT FILLING

Deep Unknown Intent Detection with Margin Loss

ACL 2019 thuiar/DeepUnkID

With margin loss, we can learn discriminative deep features by forcing the network to maximize inter-class variance and to minimize intra-class variance.

INTENT DETECTION

CM-Net: A Novel Collaborative Memory Network for Spoken Language Understanding

IJCNLP 2019 Adaxry/CM-Net

Spoken Language Understanding (SLU) mainly involves two tasks, intent detection and slot filling, which are generally modeled jointly in existing works.

INTENT DETECTION SLOT FILLING SPOKEN LANGUAGE UNDERSTANDING