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Intent Classification is the task of correctly labeling a natural language utterance from a predetermined set of intents

Source: Multi-Layer Ensembling Techniques for Multilingual Intent Classification

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Latest papers without code

Hierarchical Modeling for Out-of-Scope Domain and Intent Classification

30 Apr 2021

User queries for a real-world dialog system may sometimes fall outside the scope of the system's capabilities, but appropriate system responses will enable smooth processing throughout the human-computer interaction.

GENERAL CLASSIFICATION INTENT CLASSIFICATION MULTI-TASK LEARNING

Fuzzy Classification of Multi-intent Utterances

22 Apr 2021

In this work, we propose a scheme to address the ambiguity in single-intent as well as multi-intent natural language utterances by creating degree memberships over fuzzified intent classes.

GENERAL CLASSIFICATION INTENT CLASSIFICATION

"What's The Context?" : Long Context NLM Adaptation for ASR Rescoring in Conversational Agents

21 Apr 2021

Neural Language Models (NLM), when trained and evaluated with context spanning multiple utterances, have been shown to consistently outperform both conventional n-gram language models and NLMs that use limited context.

INTENT CLASSIFICATION LANGUAGE MODELLING NATURAL LANGUAGE UNDERSTANDING

Data Augmentation for Voice-Assistant NLU using BERT-based Interchangeable Rephrase

16 Apr 2021

We introduce a data augmentation technique based on byte pair encoding and a BERT-like self-attention model to boost performance on spoken language understanding tasks.

DATA AUGMENTATION INTENT CLASSIFICATION SEMANTIC SIMILARITY SEMANTIC TEXTUAL SIMILARITY SPOKEN LANGUAGE UNDERSTANDING VOICE ASSISTANT

Integration of Pre-trained Networks with Continuous Token Interface for End-to-End Spoken Language Understanding

15 Apr 2021

We propose a simple and robust integration method for the E2E SLU network with novel Interface, Continuous Token Interface (CTI), the junctional representation of the ASR and NLU networks when both networks are pre-trained with the same vocabulary.

INTENT CLASSIFICATION KNOWLEDGE DISTILLATION LANGUAGE MODELLING MULTI-TASK LEARNING SLOT FILLING SPOKEN LANGUAGE UNDERSTANDING

On the Robustness of Goal Oriented Dialogue Systems to Real-world Noise

14 Apr 2021

Goal oriented dialogue systems, that interact in real-word environments, often encounter noisy data.

DATA AUGMENTATION GOAL-ORIENTED DIALOGUE SYSTEMS INTENT CLASSIFICATION

Few-shot Intent Classification and Slot Filling with Retrieved Examples

12 Apr 2021

Few-shot learning arises in important practical scenarios, such as when a natural language understanding system needs to learn new semantic labels for an emerging, resource-scarce domain.

FEW-SHOT LEARNING GENERAL CLASSIFICATION INTENT CLASSIFICATION NATURAL LANGUAGE UNDERSTANDING SLOT FILLING

Intent Recognition and Unsupervised Slot Identification for Low Resourced Spoken Dialog Systems

3 Apr 2021

We build a word-free natural language understanding module that does intent recognition and slot identification from these phonetic transcription.

DATA AUGMENTATION GENERAL CLASSIFICATION INTENT CLASSIFICATION NATURAL LANGUAGE UNDERSTANDING SPOKEN LANGUAGE UNDERSTANDING

Industry Scale Semi-Supervised Learning for Natural Language Understanding

29 Mar 2021

This paper presents a production Semi-Supervised Learning (SSL) pipeline based on the student-teacher framework, which leverages millions of unlabeled examples to improve Natural Language Understanding (NLU) tasks.

INTENT CLASSIFICATION KNOWLEDGE DISTILLATION NAMED ENTITY RECOGNITION NATURAL LANGUAGE UNDERSTANDING

NUBOT: Embedded Knowledge Graph With RASA Framework for Generating Semantic Intents Responses in Roman Urdu

20 Feb 2021

The understanding of the human language is quantified by identifying intents and entities.

CHATBOT INTENT CLASSIFICATION