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Spoken SQuAD: A Study of Mitigating the Impact of Speech Recognition Errors on Listening Comprehension

arXiv 1804.00320 ↗First posted 1 Apr 2018cs.CLcited by 74

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Abstract (arXiv)

Reading comprehension has been widely studied. One of the most representative reading comprehension tasks is Stanford Question Answering Dataset (SQuAD), on which machine is already comparable with human. On the other hand, accessing large collections of multimedia or spoken content is much more difficult and time-consuming than plain text content for humans. It's therefore highly attractive to develop machines which can automatically understand spoken content. In this paper, we propose a new listening comprehension task - Spoken SQuAD. On the new task, we found that speech recognition errors have catastrophic impact on machine comprehension, and several approaches are proposed to mitigate the impact.

Key facts. Cited by 74 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Apr 2018.

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Citing papers per year: 2021: 9; 2022: 7; 2023: 6; 2024: 15; 2025: 16; 2026: 21.

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  1. 2021QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehensioncited by 91
  2. 2024SD-Eval: A Benchmark Dataset for Spoken Dialogue Understanding Beyond Wordscited by 67
  3. 2025Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generationcited by 42
  4. 2021Self-supervised Contrastive Cross-Modality Representation Learning for Spoken Question Answeringcited by 39
  5. 2022End-to-end Spoken Conversational Question Answering: Task, Dataset and Modelcited by 37
  6. 2021SD-QA: Spoken Dialectal Question Answering for the Real Worldcited by 36
  7. 2022SLUE Phase-2: A Benchmark Suite of Diverse Spoken Language Understanding Taskscited by 34
  8. 2021Self-supervised Dialogue Learning for Spoken Conversational Question Answeringcited by 27
  9. 2021M5Product: Self-harmonized Contrastive Learning for E-commercial Multi-modal Pretrainingcited by 26
  10. 2021NoiseQA: Challenge Set Evaluation for User-Centric Question Answeringcited by 25
  11. 2021Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answeringcited by 20
  12. 2025WavRAG: Audio-Integrated Retrieval Augmented Generation for Spoken Dialogue Modelscited by 18
38 more
  1. 2023HeySQuAD: A Spoken Question Answering Datasetcited by 16
  2. 2021Revisiting the Boundary between ASR and NLU in the Age of Conversational Dialog Systemscited by 15
  3. 2022DUAL: Discrete Spoken Unit Adaptive Learning for Textless Spoken Question Answeringcited by 15
  4. 2024Speech Retrieval-Augmented Generation without Automatic Speech Recognitioncited by 14
  5. 2023LibriSQA: A Novel Dataset and Framework for Spoken Question Answering with Large Language Modelscited by 13
  6. 2024SpeechDPR: End-to-End Spoken Passage Retrieval for Open-Domain Spoken Question Answeringcited by 12
  7. 2024Enhancing Low-Resource Language and Instruction Following Capabilities of Audio Language Modelscited by 10
  8. 2024On the Evaluation of Speech Foundation Models for Spoken Language Understandingcited by 9
  9. 2023GSQA: An End-to-End Model for Generative Spoken Question Answeringcited by 8
  10. 2024Towards ASR Robust Spoken Language Understanding Through In-Context Learning With Word Confusion Networkscited by 8
  11. 2024Contrastive Learning for Task-Independent SpeechLLM-Pretrainingcited by 8
  12. 2025SpokenNativQA: Multilingual Everyday Spoken Queries for LLMscited by 8
  13. 2024MERaLiON-AudioLLM: Bridging Audio and Language with Large Language Modelscited by 7
  14. 2025WearVox: An Egocentric Multichannel Voice Assistant Benchmark for Wearablescited by 7
  15. 2026Uncertainty Quantification for Multimodal Large Language Models with Incoherence-adjusted Semantic Volumecited by 7
  16. 2022On the Impact of Speech Recognition Errors in Passage Retrieval for Spoken Question Answeringcited by 6
  17. 2025The Role of Prosody in Spoken Question Answeringcited by 6
  18. 2025Measuring the Effect of Transcription Noise on Downstream Language Understanding Taskscited by 6
  19. 2022Video-Guided Curriculum Learning for Spoken Video Groundingcited by 5
  20. 2025NAVER LABS Europe Submission to the Instruction-following Trackcited by 5
  21. 2023MeeQA: Natural Questions in Meeting Transcriptscited by 4
  22. 2023The Interpreter Understands Your Meaning: End-to-end Spoken Language Understanding Aided by Speech Translationcited by 4
  23. 2024Multi-Modal Retrieval For Large Language Model Based Speech Recognitioncited by 4
  24. 2025KIT's Offline Speech Translation and Instruction Following Submission for IWSLT 2025cited by 4
  25. 2025IFEval-Audio: Benchmarking Instruction-Following Capability in Audio-based Large Language Modelscited by 4
  26. 2024Surprisingly Fragile: Assessing and Addressing Prompt Instability in Multimodal Foundation Modelscited by 3
  27. 2024Data-Centric Improvements for Enhancing Multi-Modal Understanding in Spoken Conversation Modelingcited by 3
  28. 2025NUTSHELL: A Dataset for Abstract Generation from Scientific Talkscited by 3
  29. 2026SpeechMapper: Speech-to-text Embedding Projector for LLMscited by 3
  30. 2022EVI: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identificationcited by 2
  31. 2022Learning Action-Effect Dynamics for Hypothetical Vision-Language Reasoning Taskcited by 2
  32. 2024Zero-Shot End-To-End Spoken Question Answering In Medical Domaincited by 2
  33. 2024MoWE-Audio: Multitask AudioLLMs with Mixture of Weak Encoderscited by 2
  34. 2024A Multimodal Dense Retrieval Approach for Speech-Based Open-Domain Question Answeringcited by 2
  35. 2025Standard-to-Dialect Transfer Trends Differ across Text and Speech: A Case Study on Intent and Topic Classification in German Dialectscited by 2
  36. 2025End-to-end Contrastive Language-Speech Pretraining Model For Long-form Spoken Question Answeringcited by 2
  37. 2025Roles of MLLMs in Visually Rich Document Retrieval for RAG: A Surveycited by 2
  38. 2021An Initial Investigation of Non-Native Spoken Question-Answeringcited by 1

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