Detecting language impairment using ELIEC

Automatically Derived Spoken Language Markers for Detecting Mild Cognitive Impairment

Speech produced by subjects during neuropsychological exams can provide markers other than test performance, via spoken language characteristics that discriminate between subject groups. We present preliminary results on the utility of such markers, automatically derived from spoken responses to narrative recall tests, in discriminating between healthy elderly and subjects with Mild Cognitive I...

Detecting Unknown Network Attacks Using Language Models

We propose a method for network intrusion detection based on language models such as n-grams and words. Our method proceeds by extracting these models from TCP connection payloads and applying unsupervised anomaly detection. The essential part of our approach is linear-time computation of similarity measures between language models stored in trie data structures. Results of our experiments cond...

Detecting Cognitive Impairment and Dementia in Deaf People: The British Sign Language Cognitive Screening Test.

To provide accurate diagnostic screening of deaf people who use signed communication, cognitive tests must be devised in signed languages with normative deaf samples. This article describes the development of the first screening test for the detection of cognitive impairment and dementia in deaf signers. The British Sign Language Cognitive Screening Test uses standardized video administration t...

Language Impairment in Zulu

Detecting Speculative Language Using Syntactic Dependencies and Logistic Regression

In this paper we describe our approach to the CoNLL 2010 shared task on detecting speculative language in biomedical text. We treat the detection of sentences containing uncertain information (Task1) as a token classification task since the existence or absence of cues determines the sentence label. We distinguish words that have speculative and non-speculative meaning by employing syntactic fe...