# Knowledge Distillation for Improved Accuracy in Spoken Question Answering

arXiv: https://arxiv.org/abs/2010.11067 · HTML: https://mlsanity.com/paper/2010.11067/

## Key facts

- Cited by 31 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Oct 2020.

## Built on by (most cited first, 30 of 31)

- [SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentation](https://mlsanity.com/paper/2108.06227/) (2021)
- [Auffusion: Leveraging the Power of Diffusion and Large Language Models for Text-to-Audio Generation](https://mlsanity.com/paper/2401.01044/) (2024)
- [Momentum Contrastive Voxel-wise Representation Learning for Semi-supervised Volumetric Medical Image Segmentation](https://mlsanity.com/paper/2105.07059/) (2021)
- [Auto-Encoding Knowledge Graph for Unsupervised Medical Report Generation](https://mlsanity.com/paper/2111.04318/) (2021)
- [Self-supervised Contrastive Cross-Modality Representation Learning for Spoken Question Answering](https://mlsanity.com/paper/2109.03381/) (2021)
- [End-to-end Spoken Conversational Question Answering: Task, Dataset and Model](https://mlsanity.com/paper/2204.14272/) (2022)
- [Why Prompt Design Matters and Works: A Complexity Analysis of Prompt Search Space in LLMs](https://mlsanity.com/paper/2503.10084/) (2025)
- [Maximum Bayes Smatch Ensemble Distillation for AMR Parsing](https://mlsanity.com/paper/2112.07790/) (2021)
- [Self-supervised Dialogue Learning for Spoken Conversational Question Answering](https://mlsanity.com/paper/2106.02182/) (2021)
- [HeySQuAD: A Spoken Question Answering Dataset](https://mlsanity.com/paper/2304.13689/) (2023)
- [Aligning Source Visual and Target Language Domains for Unpaired Video Captioning](https://mlsanity.com/paper/2211.12148/) (2022)
- [A Decentralized Reinforcement Learning Framework for Efficient Passage of Emergency Vehicles](https://mlsanity.com/paper/2111.00278/) (2021)
- [EMVLight: a Multi-agent Reinforcement Learning Framework for an Emergency Vehicle Decentralized Routing and Traffic Signal Control System](https://mlsanity.com/paper/2206.13441/) (2022)
- [GSQA: An End-to-End Model for Generative Spoken Question Answering](https://mlsanity.com/paper/2312.09781/) (2023)
- [MEGAN: Memory Enhanced Graph Attention Network for Space-Time Video Super-Resolution](https://mlsanity.com/paper/2110.15327/) (2021)
- [Bridging the Gap between Language Models and Cross-Lingual Sequence Labeling](https://mlsanity.com/paper/2204.05210/) (2022)
- [Measuring the Effect of Transcription Noise on Downstream Language Understanding Tasks](https://mlsanity.com/paper/2502.13645/) (2025)
- [Graph-in-Graph Network for Automatic Gene Ontology Description Generation](https://mlsanity.com/paper/2206.05311/) (2022)
- [A Variance-Preserving Interpolation Approach for Diffusion Models with Applications to Single Channel Speech Enhancement and Recognition](https://mlsanity.com/paper/2405.16952/) (2024)
- [UniHGKR: Unified Instruction-aware Heterogeneous Knowledge Retrievers](https://mlsanity.com/paper/2410.20163/) (2024)
- [Leveraging Pretrained ASR Encoders for Effective and Efficient End-to-End Speech Intent Classification and Slot Filling](https://mlsanity.com/paper/2307.07057/) (2023)
- [Deep Active Audio Feature Learning in Resource-Constrained Environments](https://mlsanity.com/paper/2308.13201/) (2023)
- [Computation and Parameter Efficient Multi-Modal Fusion Transformer for Cued Speech Recognition](https://mlsanity.com/paper/2401.17604/) (2024)
- [ELP-Adapters: Parameter Efficient Adapter Tuning for Various Speech Processing Tasks](https://mlsanity.com/paper/2407.21066/) (2024)
- [The End of Reward Engineering: How LLMs Are Redefining Multi-Agent Coordination](https://mlsanity.com/paper/2601.08237/) (2026)
- [Zero-Shot End-To-End Spoken Question Answering In Medical Domain](https://mlsanity.com/paper/2406.05876/) (2024)
- [A Multimodal Dense Retrieval Approach for Speech-Based Open-Domain Question Answering](https://mlsanity.com/paper/2409.13483/) (2024)
- [Calibrate and Refine! A Novel and Agile Framework for ASR-error Robust Intent Detection](https://mlsanity.com/paper/2205.11008/) (2022)
- [Natural Response Generation for Chinese Reading Comprehension](https://mlsanity.com/paper/2302.08817/) (2023)
- [Spoken question answering for visual queries](https://mlsanity.com/paper/2505.23308/) (2025)

## Abstract (arXiv)

Spoken question answering (SQA) is a challenging task that requires the machine to fully understand the complex spoken documents. Automatic speech recognition (ASR) plays a significant role in the development of QA systems. However, the recent work shows that ASR systems generate highly noisy transcripts, which critically limit the capability of machine comprehension on the SQA task. To address the issue, we present a novel distillation framework. Specifically, we devise a training strategy to perform knowledge distillation (KD) from spoken documents and written counterparts. Our work makes a step towards distilling knowledge from the language model as a supervision signal to lead to better student accuracy by reducing the misalignment between automatic and manual transcriptions. Experiments demonstrate that our approach outperforms several state-of-the-art language models on the Spoken-SQuAD dataset.