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Spoken Language Understanding

11 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

ISO-Standard Domain-Independent Dialogue Act Tagging for Conversational Agents

COLING 2018 ColingPaper2018/DialogueAct-Tagger

Dialogue Act (DA) tagging is crucial for spoken language understanding systems, as it provides a general representation of speakers' intents, not bound to a particular dialogue system.

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

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

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