Improving Detection of Alzheimer's Disease Using Automatic Speech Recognition to Identify High-Quality Segments for More Robust Feature Extraction

@inproceedings{Pan2020ImprovingDO,
  title={Improving Detection of Alzheimer's Disease Using Automatic Speech Recognition to Identify High-Quality Segments for More Robust Feature Extraction},
  author={Yilin Pan and Bahman Mirheidari and Markus Reuber and Annalena Venneri and Daniel J. Blackburn and Heidi Christensen},
  booktitle={INTERSPEECH},
  year={2020}
}
Speech and language based automatic dementia detection is of interest due to it being non-invasive, low-cost and potentially able to aid diagnosis accuracy. The collected data are mostly audio recordings of spoken language and these can be used directly for acoustic-based analysis. To extract linguistic-based information, an automatic speech recognition (ASR) system is used to generate transcriptions. However, the extraction of reliable acoustic features is difficult when the acoustic quality… 

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