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Spoken Language Understanding

9 papers with code · Speech

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Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces

25 May 2018snipsco/snips-nlu

This paper presents the machine learning architecture of the Snips Voice Platform, a software solution to perform Spoken Language Understanding on microprocessors typical of IoT devices.

SPEECH RECOGNITION SPOKEN LANGUAGE UNDERSTANDING

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

Fully Statistical Neural Belief Tracking

ACL 2018 nmrksic/neural-belief-tracker

This paper proposes an improvement to the existing data-driven Neural Belief Tracking (NBT) framework for Dialogue State Tracking (DST).

DIALOGUE MANAGEMENT DIALOGUE STATE TRACKING SPOKEN LANGUAGE UNDERSTANDING WORD EMBEDDINGS

Speech Model Pre-training for End-to-End Spoken Language Understanding

7 Apr 2019lorenlugosch/pretrain_speech_model

Whereas conventional spoken language understanding (SLU) systems map speech to text, and then text to intent, end-to-end SLU systems map speech directly to intent through a single trainable model.

SPOKEN LANGUAGE UNDERSTANDING

Dynamic Time-Aware Attention to Speaker Roles and Contexts for Spoken Language Understanding

30 Sep 2017MiuLab/Time-SLU

However, the previous model only paid attention to the content in history utterances without considering their temporal information and speaker roles.

DIALOGUE STATE TRACKING SPOKEN LANGUAGE UNDERSTANDING

Graph-Based Semi-Supervised Conditional Random Fields For Spoken Language Understanding Using Unaligned Data

ALTA 2014 maxxkia/g-ssl-crf

We experiment graph-based Semi-Supervised Learning (SSL) of Conditional Random Fields (CRF) for the application of Spoken Language Understanding (SLU) on unaligned data.

SPOKEN LANGUAGE UNDERSTANDING

Unsupervised Transfer Learning for Spoken Language Understanding in Intelligent Agents

13 Nov 2018sxjscience/GluonNLP-Slot-Filling

Our findings suggest unsupervised pre-training on a large corpora of unlabeled utterances leads to significantly better SLU performance compared to training from scratch and it can even outperform conventional supervised transfer.

LANGUAGE MODELLING SPOKEN LANGUAGE UNDERSTANDING TRANSFER LEARNING