Orith Toledo-Ronen

Automatic speech analysis for the assessment of patients with predementia and Alzheimer's disease

To evaluate the interest of using automatic speech analyses for the assessment of mild cognitive impairment (MCI) and early‐stage Alzheimers disease (AD).

Multi-modal biometrics for mobile authentication

User authentication in the context of a secure transaction needs to be continuously evaluated for the risks associated with the transaction authorization. The situation becomes even more critical when there are regulatory compliance requirements. Need for such systems have grown dramatically with the introduction of smart mobile devices which make it far easier for the user to complete such transaction quickly but with a huge exposure to risk. Biometrics can play a very significant role in addressing such problems as a key indicator of the user identity and thus reducing the risk of fraud. While unimodal biometrics authentication systems are being increasingly experimented by mainstream mobile system manufacturers (e.g., fingerprint in iOS), we explore various opportunities of reducing risk in a multimodal biometrics system. The multimodal system is based on fusion of several biometrics combined with a policy manager. A new biometric modality: chirography which is based on user writing on multi-touch screens using their finger is introduced. Coupling with chirography, we also use two other biometrics: face and voice. Our fusion strategy is based on inter-modality score level fusion that takes into account a voice quality measure. The proposed system has been evaluated on an in-house database that reflects the latest smart mobile devices. On this database, we demonstrate a very high accuracy multi-modal authentication system reaching an EER of 0.1% in an office environment and an EER of 0.5% in challenging noisy environments.

Expert Stance Graphs for Computational Argumentation.

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 automatic and semi-automatic methods for building the graph are explored, and manual assessment validates the high accuracy of the resulting graph.

THE DEM@CARE PROJECT SPEECH RECORDING AND AUTOMATIC ANALYSIS FOR THE ASSESSMENT OF ALZHEIMER DISEASE AND RELATED DISORDERS

increase the risk for developing AD. Results: The study population consisted of 183 MCI patients at baseline. At follow-up, 74 patients were stable and 109 patients progressed to AD. The presence of significant depressive symptoms in MCI as measured by the CSDD (HR: 2.06; 95% CI: 1.23 3.44; p1⁄40.011) and the GDS-30 (HR: 1.77; 95% CI: 1.10 2.85; p1⁄40.025) were associated with an increased the risk of progression to AD. The severity of depressive symptoms as measured by the GDS-30 was a predictor for progression too (HR: 1.06; 95% CI: 1.01 1.11; p1⁄40.020). Furthermore, also the severity of agitated behavior, especially verbal agitation, and the presence of purposeless activity were associated risk factors for progression, whereas diurnal rhythm disturbances in our study was associated with a decreased risk of progression. Conclusions: Depressive symptoms in MCI appear to be associated with an increased risk of progression to AD.

Speech processing and retrieval in a personal memory aid system for the elderly

The paper presents a new application of automatic speech processing in the Ambient Assisted Living area, developed in the course of a three year research project. Recording and automatic processing of spoken conversations plays a major role in this solution enabling effective search in a personal audio archive and fast browsing of conversations. Processing of elderly conversational speech recorded by a distant PDA microphone poses a great challenge. The speech processing flow includes transcription, speaker tracking and combined indexing and search of spoken terms and participating speakers identity extracted from the audio. We present the entire application and individual speech processing components as well as evaluation results of the individual components and of the end-to-end spoken information retrieval solution.