Papers by Nicolas Langer
ZuCo 2.0: A Dataset of Physiological Recordings During Natural Reading and Annotation (2020.lrec-1)
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| Challenge: | a new dataset of eye-tracking and electroencephalography captures language understanding . eye movement data provides millisecond-accurate records of where humans look when reading . |
| Approach: | They recorded and preprocessed eye-tracking and electroencephalography data during natural reading and during annotation. |
| Outcome: | The study combines eye-tracking and electroencephalography to capture the reading process . the data can be used to evaluate state-of-the-art machine learning systems . |
The Influence of Automatic Speech Recognition on Linguistic Features and Automatic Alzheimer’s Disease Detection from Spontaneous Speech (2024.lrec-main)
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| Challenge: | Existing biomarkers for AD diagnosis can only be applied to relatively small sample sizes due to limited availability, excessive costs and invasive nature. |
| Approach: | They compare automatic speech recognition systems in terms of Word Error Rate (WER) using a publicly available benchmark dataset of speech recordings of AD patients and controls. |
| Outcome: | The proposed method improves classification performance by replacing manual transcriptions with ASR output. |
Linguistic Features Extracted by GPT-4 Improve Alzheimer’s Disease Detection based on Spontaneous Speech (2025.coling-main)
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| Challenge: | Large language models (LLMs) have enabled powerful new possibilities for semantic text analysis. |
| Approach: | They leverage GPT-4 to extract five semantic features from transcripts of spontaneous patient speech. |
| Outcome: | The proposed model significantly improves detection of AD in manually transcribed and automatically generated transcripts. |