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Intent Classification

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

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 161–170 of 344 papers

Title	Date	Tasks	Status	Hype
Three-Module Modeling For End-to-End Spoken Language Understanding Using Pre-trained DNN-HMM-Based Acoustic-Phonetic Model	Apr 7, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Quick Starting Dialog Systems with Paraphrase Generation	Apr 6, 2022	intent-classificationIntent Classification	—Unverified	0
Data Augmentation for Intent Classification with Off-the-shelf Large Language Models	Apr 5, 2022	Data Augmentationintent-classification	CodeCode Available	1
LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERT	Mar 29, 2022	AllAutomatic Speech Recognition	CodeCode Available	1
A Speech Representation Anonymization Framework via Selective Noise Perturbation	Mar 26, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	0
Towards Textual Out-of-Domain Detection without In-Domain Labels	Mar 22, 2022	Contrastive Learningintent-classification	—Unverified	0
Bi-directional Joint Neural Networks for Intent Classification and Slot Filling	Feb 26, 2022	Classificationintent-classification	—Unverified	0
A new data augmentation method for intent classification enhancement and its application on spoken conversation datasets	Feb 21, 2022	Active LearningData Augmentation	—Unverified	0
When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computing	Feb 17, 2022	ClassificationCPU	—Unverified	0
pNLP-Mixer: an Efficient all-MLP Architecture for Language	Feb 9, 2022	Allintent-classification	CodeCode Available	1

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All datasets SLURP MASSIVE KUAKE-QIC ORCAS-I

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	TDT 0-8	Accuracy (%)	90.07	—	Unverified
2	Partially Fine-tuned HuBERT	Accuracy (%)	87.51	—	Unverified
3	Multi-SLURP	Accuracy (%)	78.33	—	Unverified
4	Finstreder (Conformer)	Accuracy (%)	53.11	—	Unverified
5	Finstreder (Quartznet)	Accuracy (%)	43.15	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	mT5 Base (encoder-only)	Intent Accuracy	86.1	—	Unverified
2	mT5 Base (text-to-text)	Intent Accuracy	85.3	—	Unverified
3	XLM-R Base	Intent Accuracy	85.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RoBERTa-wwm-ext-base	Accuracy	85.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BERT (query + URL)	F1-score	0.77	—	Unverified