An Analysis of Perplexity to Reveal the Effects of Alzheimer's Disease on Language - Wankerl, Sebastian; Nöth, Elmar; Evert, Stephanie (ITG-Fachbericht 267: Speech Communication, 2016)

Automatic Diagnosis of Alzheimer's Disease Using Neural Network Language Models - Fritsch, Julian; Wankerl, Sebastian; Nöth, Elmar (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2019)
In today's aging society, the number of neurodegenerative diseases such as Alzheimer's disease (AD) increases. Reliable tools for automatic early screening as well as monitoring of AD patients are necessary. For that, semantic deficits have been shown to be useful indicators. We present a way to significantly improve the method introduced by Wankerl et al. [1]. The purely statistical approach of n-gram language models (LMs) is enhanced by using the rwthlm toolkit to create neural network language models (NNLMs) with Long Short Term-Memory (LSTM) cells. The prediction is solely based on evaluating the perplexity of transliterations of descriptions of the Cookie Theft picture from DementiaBank's Pitt Corpus. Each transliteration is evaluated on LMs of both control and Alzheimer speakers in a leave-one-speaker-out cross-validation scheme. The resulting perplexity values reveal enough discrepancy to classify patients on just those two values with an accuracy of 85.6% at equal-error-rate.
CRIS-Team Scopus Importer:2019-07-23
Keywords: Alzheimer's disease; automatic diagnosis; language models; Long-Short Term Memory; neural network language models

Reliable measures of syntactic and lexical complexity: The case of Iris Murdoch - Evert, Stephanie; Wankerl, Sebastian; Nöth, Elmar (Proceedings of the Corpus Linguistics 2017 Conference, 2017)
In this paper, we propose a novel methodology for the computation of reliable confidence intervals and significance tests for measures of linguistic complexity, inspired by ideas from bootstrapping and cross-validation. As an illustration, we apply the new method to the detection of early symptoms of Alzheimer's disease in the novels of Iris Murdoch, showing that most of the differences observed in previous work are not signficant and can indeed be accounted for by sampling variation.
Keywords: LNRE; lexical statistics

Visual comparison of speaker groups - Wankerl, Sebastian; Hönig, Florian Thomas; Batliner, Anton; Orozco Arroyave, Juan Rafael; Nöth, Elmar (16th Annual Conference of the International Speech Communication Association, INTERSPEECH 2015, 2015)
We describe a generic tool for visualising differences between two groups of speakers who produce a given word sequence. We do this by first time-aligning all recordings and then aggregating time-varying information within each group. By that, we can display prototypical loudness and tempo contours, and also spectrograms, together with information on variability and group effect size over time. An optional user-supplied segmentation (just needed for one of the recordings) can be used to relate local differences to individual phonemes. The system is validated with a group of speakers with Parkinson's disease and an age-matched control group. It will be provided as an opensource software package to the community.
Keywords: Acoustic features; Atypical speech; Interpretation; Paralinguistics; Pathological speech; Visualization