Orith Toledo-Ronen

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BACKGROUND To evaluate the interest of using automatic speech analyses for the assessment of mild cognitive impairment (MCI) and early-stage Alzheimer's disease (AD). METHODS Healthy elderly control (HC) subjects and patients with MCI or AD were recorded while performing several short cognitive vocal tasks. The voice recordings were processed, and the(More)
This paper describes a study of a protocol and a system for automatic detection and status tracking of early-stage dementia and Mild Cognitive Impairment (MCI), from speech and voice recordings. The research has been performed in the scope of the EU FP7 Dem@Care project. We describe the speech and voice recording protocol, different families of vocal(More)
We present a method that identifies speakers that are likely to have a high false-reject rate in a text-dependent speaker verification system (“goats”). The method normally uses only the enrollment data to perform this task. We begin with extracting an appropriate feature from each enrollment session. We then rank all the enrollment sessions in the system(More)
In this paper, we propose a Modulation Spectrum-based manageable feature set for detection of depressed speech. Modulation Spectrum (MS) is obtained from the conventional speech spectrogram by spectral analysis along the temporal trajectories of the acoustic frequency bins. While MS representation of speech provides rich and high-dimensional joint frequency(More)
Confidence scoring is an important component in speaker diarization systems, both for offline speech analytics and for online diarization that are required to produce the speaker segmentation from very little audio. This paper proposes a confidence measure for speaker diarization based on the spectral ratio of the eigenvalues of the Principal Component(More)
We describe the construction of an Expert Stance Graph, a novel, large-scale knowledge resource that encodes the stance of more than 100,000 experts towards a variety of controversial topics. We suggest that this graph may be valuable for various fundamental tasks in computational argumentation. Experts and topics in our graph are Wikipedia entries. Both(More)