# Impact of ASR on Alzheimer's Disease Detection: All Errors are Equal, but Deletions are More Equal than Others

arXiv: https://arxiv.org/abs/1904.01684 · HTML: https://mlsanity.com/paper/1904.01684/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Apr 2019.

## Built on by (most cited first, 8 of 8)

- [Comparing Acoustic-based Approaches for Alzheimer's Disease Detection](https://mlsanity.com/paper/2106.01555/) (2021)
- [Useful Blunders: Can Automated Speech Recognition Errors Improve Downstream Dementia Classification?](https://mlsanity.com/paper/2401.05551/) (2024)
- [Measuring the Effect of Transcription Noise on Downstream Language Understanding Tasks](https://mlsanity.com/paper/2502.13645/) (2025)
- [Robustness and Sensitivity of BERT Models Predicting Alzheimer's Disease from Text](https://mlsanity.com/paper/2109.11888/) (2021)
- [Influence of ASR and Language Model on Alzheimer's Disease Detection](https://mlsanity.com/paper/2110.15704/) (2021)
- [The Far Side of Failure: Investigating the Impact of Speech Recognition Errors on Subsequent Dementia Classification](https://mlsanity.com/paper/2211.07430/) (2022)
- [Not All Errors Are Equal: Investigation of Speech Recognition Errors in Alzheimer's Disease Detection](https://mlsanity.com/paper/2412.06332/) (2024)
- [The Impact of ASR on the Automatic Analysis of Linguistic Complexity and Sophistication in Spontaneous L2 Speech](https://mlsanity.com/paper/2104.08529/) (2021)

## Abstract (arXiv)

Automatic Speech Recognition (ASR) is a critical component of any fully-automated speech-based dementia detection model. However, despite years of speech recognition research, little is known about the impact of ASR accuracy on dementia detection. In this paper, we experiment with controlled amounts of artificially generated ASR errors and investigate their influence on dementia detection. We find that deletion errors affect detection performance the most, due to their impact on the features of syntactic complexity and discourse representation in speech. We show the trend to be generalisable across two different datasets for cognitive impairment detection. As a conclusion, we propose optimising the ASR to reflect a higher penalty for deletion errors in order to improve dementia detection performance.