mlsanityData to 14 Oct 2026

A Survey on Spoken Language Understanding: Recent Advances and New Frontiers

arXiv 2103.03095 ↗First posted 4 Mar 2021cs.CLcited by 53

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Abstract (arXiv)

Spoken Language Understanding (SLU) aims to extract the semantics frame of user queries, which is a core component in a task-oriented dialog system. With the burst of deep neural networks and the evolution of pre-trained language models, the research of SLU has obtained significant breakthroughs. However, there remains a lack of a comprehensive survey summarizing existing approaches and recent trends, which motivated the work presented in this article. In this paper, we survey recent advances and new frontiers in SLU. Specifically, we give a thorough review of this research field, covering different aspects including (1) new taxonomy: we provide a new perspective for SLU filed, including single model vs. joint model, implicit joint modeling vs. explicit joint modeling in joint model, non pre-trained paradigm vs. pre-trained paradigm;(2) new frontiers: some emerging areas in complex SLU as well as the corresponding challenges; (3) abundant open-source resources: to help the community, we have collected, organized the related papers, baseline projects and leaderboard on a public website where SLU researchers could directly access to the recent progress. We hope that this survey can shed a light on future research in SLU field.

Key facts. Cited by 53 papers in the map (data through 14 Oct 2026). Builds on 33 of its 63 references that are in the map. First posted on arXiv 4 Mar 2021.

Builds on

33 of 63 references.

References · 33

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2018Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfacescited by 377
  3. 2019BERT for Joint Intent Classification and Slot Fillingcited by 196
  4. 2017A Survey on Dialogue Systems: Recent Advances and New Frontierscited by 162
  5. 2016Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Fillingcited by 137
  6. 2018Cross-Lingual Transfer Learning for Multilingual Task Oriented Dialogcited by 125
  7. 2019A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understandingcited by 107
  8. 2019A Novel Bi-directional Interrelated Model for Joint Intent Detection and Slot Fillingcited by 85
  9. 2020End-to-End Slot Alignment and Recognition for Cross-Lingual NLUcited by 83
  10. 2020Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Networkcited by 83
  11. 2020CoSDA-ML: Multi-Lingual Code-Switching Data Augmentation for Zero-Shot Cross-Lingual NLPcited by 79
  12. 2018Joint Slot Filling and Intent Detection via Capsule Neural Networkscited by 73
21 more
  1. 2020Discovering New Intents with Deep Aligned Clusteringcited by 68
  2. 2020A Co-Interactive Transformer for Joint Slot Filling and Intent Detectioncited by 61
  3. 2019Discovering New Intents via Constrained Deep Adaptive Clustering with Cluster Refinementcited by 56
  4. 2020Deep Open Intent Classification with Adaptive Decision Boundarycited by 56
  5. 2018A Bi-model based RNN Semantic Frame Parsing Model for Intent Detection and Slot Fillingcited by 53
  6. 2020Recent Neural Methods on Slot Filling and Intent Classification for Task-Oriented Dialogue Systems: A Surveycited by 51
  7. 2019Attention-Informed Mixed-Language Training for Zero-shot Cross-lingual Task-oriented Dialogue Systemscited by 42
  8. 2017Towards Zero-Shot Frame Semantic Parsing for Domain Scalingcited by 40
  9. 2019Robust Zero-Shot Cross-Domain Slot Filling with Example Valuescited by 38
  10. 2020Coach: A Coarse-to-Fine Approach for Cross-domain Slot Fillingcited by 38
  11. 2019CM-Net: A Novel Collaborative Memory Network for Spoken Language Understandingcited by 34
  12. 2016Leveraging Sentence-level Information with Encoder LSTM for Semantic Slot Fillingcited by 25
  13. 2019Multi-lingual Intent Detection and Slot Filling in a Joint BERT-based Modelcited by 24
  14. 2020Few-shot Learning for Multi-label Intent Detectioncited by 20
  15. 2016Joint Online Spoken Language Understanding and Language Modeling with Recurrent Neural Networkscited by 19
  16. 2018OneNet: Joint Domain, Intent, Slot Prediction for Spoken Language Understandingcited by 13
  17. 2017Sequential Dialogue Context Modeling for Spoken Language Understandingcited by 11
  18. 2020Dialogue State Induction Using Neural Latent Variable Modelscited by 10
  19. 2020Injecting Word Information with Multi-Level Word Adapter for Chinese Spoken Language Understandingcited by 7
  20. 2017Multi-Domain Adversarial Learning for Slot Filling in Spoken Language Understandingcited by 6
  21. 2020Multi-Domain Spoken Language Understanding Using Domain- and Task-Aware Parameterizationcited by 4

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 6; 2022: 10; 2023: 15; 2024: 9; 2025: 8; 2026: 5.

53 papers.

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  1. 2024Large Language Models Meet NLP: A Surveycited by 103
  2. 2023Textually Pretrained Speech Language Modelscited by 101
  3. 2024Recent Advances in Speech Language Models: A Surveycited by 87
  4. 2021A Survey on Dialogue Summarization: Recent Advances and New Frontierscited by 51
  5. 2022A Survey of Multi-task Learning in Natural Language Processing: Regarding Task Relatedness and Training Methodscited by 42
  6. 2021GL-GIN: Fast and Accurate Non-Autoregressive Model for Joint Multiple Intent Detection and Slot Fillingcited by 33
  7. 2023A Preliminary Evaluation of ChatGPT for Zero-shot Dialogue Understandingcited by 31
  8. 2024Prompt Perturbation Consistency Learning for Robust Language Modelscited by 26
  9. 2024MIntRec2.0: A Large-scale Benchmark Dataset for Multimodal Intent Recognition and Out-of-scope Detection in Conversationscited by 26
  10. 2023Can ChatGPT Detect Intent? Evaluating Large Language Models for Spoken Language Understandingcited by 21
  11. 2023End-to-end Task-oriented Dialogue: A Survey of Tasks, Methods, and Future Directionscited by 17
  12. 2022Learning Discriminative Representations and Decision Boundaries for Open Intent Detectioncited by 15
38 more
  1. 2022GL-CLeF: A Global-Local Contrastive Learning Framework for Cross-lingual Spoken Language Understandingcited by 14
  2. 2022A Survey of Intent Classification and Slot-Filling Datasets for Task-Oriented Dialogcited by 14
  3. 2023CWCL: Cross-Modal Transfer with Continuously Weighted Contrastive Losscited by 12
  4. 2022Towards Relation Extraction From Speechcited by 10
  5. 2022UniDU: Towards A Unified Generative Dialogue Understanding Frameworkcited by 9
  6. 2022A Dynamic Graph Interactive Framework with Label-Semantic Injection for Spoken Language Understandingcited by 9
  7. 2023A Clustering Framework for Unsupervised and Semi-supervised New Intent Discoverycited by 9
  8. 2025Can Large Language Models Help Multimodal Language Analysis? MMLA: A Comprehensive Benchmarkcited by 9
  9. 2021Text is no more Enough! A Benchmark for Profile-based Spoken Language Understandingcited by 7
  10. 2023SDIF-DA: A Shallow-to-Deep Interaction Framework with Data Augmentation for Multi-modal Intent Detectioncited by 7
  11. 2024ECLM: Entity Level Language Model for Spoken Language Understanding with Chain of Intentcited by 7
  12. 2025On-Device LLMs for Home Assistant: Dual Role in Intent Detection and Response Generationcited by 7
  13. 2021Smoothing Dialogue States for Open Conversational Machine Readingcited by 6
  14. 2022ASR-Generated Text for Language Model Pre-training Applied to Speech Taskscited by 6
  15. 2023Out-of-Domain Intent Detection Considering Multi-Turn Dialogue Contextscited by 6
  16. 2025Exploring Fine-Tuning of Large Audio Language Models for Spoken Language Understanding under Limited Speech Datacited by 6
  17. 2021A Result based Portable Framework for Spoken Language Understandingcited by 4
  18. 2023Sequence-Level Knowledge Distillation for Class-Incremental End-to-End Spoken Language Understandingcited by 3
  19. 2023Speech Understanding on Tiny Devices with A Learning Cachecited by 3
  20. 2024CroPrompt: Cross-task Interactive Prompting for Zero-shot Spoken Language Understandingcited by 3
  21. 2023A Persian Benchmark for Joint Intent Detection and Slot Fillingcited by 2
  22. 2023OpenSLU: A Unified, Modularized, and Extensible Toolkit for Spoken Language Understandingcited by 2
  23. 2024Pro-HAN: A Heterogeneous Graph Attention Network for Profile-Based Spoken Language Understandingcited by 2
  24. 2025Safeguarding Privacy in Edge Speech Understanding with Tiny Foundation Modelscited by 2
  25. 2025An Efficient Task-Oriented Dialogue Policy: Evolutionary Reinforcement Learning Injected by Elite Individualscited by 2
  26. 2025MAC-SLU: Multi-Intent Automotive Cabin Spoken Language Understanding Benchmarkcited by 2
  27. 2022Calibrate and Refine! A Novel and Agile Framework for ASR-error Robust Intent Detectioncited by 1
  28. 2022ESIE-BERT: Enriching Sub-words Information Explicitly with BERT for Joint Intent Classification and SlotFillingcited by 1
  29. 2023Controllable Data Augmentation for Context-Dependent Text-to-SQLcited by 1
  30. 2024Interpretation of the Intent Detection Problem as Dynamics in a Low-dimensional Spacecited by 1
  31. 2024Transforming NLU with Babylon: A Case Study in Development of Real-time, Edge-Efficient, Multi-Intent Translation System for Automated Drive-Thru Orderingcited by 1
  32. 2025Measuring Intent Comprehension in LLMscited by 1
  33. 2021Advances in Multi-turn Dialogue Comprehension: A Surveycited by 0
  34. 2023Continual Contrastive Spoken Language Understandingcited by 0
  35. 2023Are cascade dialogue state tracking models speaking out of turn in spoken dialogues?cited by 0
  36. 2025Multi-Intent Spoken Language Understanding: Methods, Trends, and Challengescited by 0
  37. 2026Interpretability of the Intent Detection Problem: A New Approachcited by 0
  38. 2026A Generative Model for Joint Multiple Intent Detection and Slot Fillingcited by 0

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