mlsanityData to 7 Oct 2026

MedSpeak: A Knowledge Graph-Aided ASR Error Correction Framework for Spoken Medical QA

arXiv 2602.00981 ↗First posted 1 Feb 2026cs.CL cs.AIcited by 1

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Abstract (arXiv)

Spoken question-answering (SQA) systems relying on automatic speech recognition (ASR) often struggle with accurately recognizing medical terminology. To this end, we propose MedSpeak, a novel knowledge graph-aided ASR error correction framework that refines noisy transcripts and improves downstream answer prediction by leveraging both semantic relationships and phonetic information encoded in a medical knowledge graph, together with the reasoning power of LLMs. Comprehensive experimental results on benchmarks demonstrate that MedSpeak significantly improves the accuracy of medical term recognition and overall medical SQA performance, establishing MedSpeak as a state-of-the-art solution for medical SQA. The code is available at https://github.com/RainieLLM/MedSpeak.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 11 of its 15 references that are in the map. First posted on arXiv 1 Feb 2026.

Builds on

11 of 15 references.

References · 11

  1. 2025MedRAG: Enhancing Retrieval-augmented Generation with Knowledge Graph-Elicited Reasoning for Healthcare Copilotcited by 83
  2. 2023Retrieval-Augmented Text-to-Audio Generationcited by 23
  3. 2024Retrieval Augmented End-to-End Spoken Dialog Modelscited by 20
  4. 2024Speech Retrieval-Augmented Generation without Automatic Speech Recognitioncited by 14
  5. 2024Retrieval Augmented Correction of Named Entity Speech Recognition Errorscited by 10
  6. 2024Contextualization of ASR with LLM using phonetic retrieval-based augmentationcited by 10
  7. 2024Retrieval Augmented Generation in Prompt-based Text-to-Speech Synthesis with Context-Aware Contrastive Language-Audio Pretrainingcited by 9
  8. 2025GEC-RAG: Improving Generative Error Correction via Retrieval-Augmented Generation for Automatic Speech Recognition Systemscited by 5
  9. 2025Retrieval-Augmented Dialogue Knowledge Aggregation for Expressive Conversational Speech Synthesiscited by 4
  10. 2025SEAL: Speech Embedding Alignment Learning for Speech Large Language Model with Retrieval-Augmented Generationcited by 3
  11. 2024Zero-Shot End-To-End Spoken Question Answering In Medical Domaincited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Error-Aware TF-IDF Retrieval-Augmented Generation for ASR Error Correctioncited by 0

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  1. 2024The Sound of Healthcare: Improving Medical Transcription ASR Accuracy with Large Language Models
  2. 2026ReGraM: Region-First Knowledge Graph Reasoning for Medical Question Answering
  3. 2026MedMosaic: A Challenging Large Scale Benchmark of Diverse Medical Audio
  4. 2025MKG-Rank: Enhancing Large Language Models with Knowledge Graph for Multilingual Medical Question Answering
  5. 2025GraphMed-LT: Patient-Specific Graph Memory with Latent Clinical Thought Refinement for Multi-Turn Medical Conversations
  6. 2025Agentic Medical Knowledge Graphs Enhance Medical Question Answering: Bridging the Gap Between LLMs and Evolving Medical Knowledge
  7. 2025CaReAQA: A Cardiac and Respiratory Audio Question Answering Model for Open-Ended Diagnostic Reasoning
  8. 2023Improving Medical Speech-to-Text Accuracy with Vision-Language Pre-training Model