2 resultados para EMMA

em CORA - Cork Open Research Archive - University College Cork - Ireland


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Existing work in Computer Science and Electronic Engineering demonstrates that Digital Signal Processing techniques can effectively identify the presence of stress in the speech signal. These techniques use datasets containing real or actual stress samples i.e. real-life stress such as 911 calls and so on. Studies that use simulated or laboratory-induced stress have been less successful and inconsistent. Pervasive, ubiquitous computing is increasingly moving towards voice-activated and voice-controlled systems and devices. Speech recognition and speaker identification algorithms will have to improve and take emotional speech into account. Modelling the influence of stress on speech and voice is of interest to researchers from many different disciplines including security, telecommunications, psychology, speech science, forensics and Human Computer Interaction (HCI). The aim of this work is to assess the impact of moderate stress on the speech signal. In order to do this, a dataset of laboratory-induced stress is required. While attempting to build this dataset it became apparent that reliably inducing measurable stress in a controlled environment, when speech is a requirement, is a challenging task. This work focuses on the use of a variety of stressors to elicit a stress response during tasks that involve speech content. Biosignal analysis (commercial Brain Computer Interfaces, eye tracking and skin resistance) is used to verify and quantify the stress response, if any. This thesis explains the basis of the author’s hypotheses on the elicitation of affectively-toned speech and presents the results of several studies carried out throughout the PhD research period. These results show that the elicitation of stress, particularly the induction of affectively-toned speech, is not a simple matter and that many modulating factors influence the stress response process. A model is proposed to reflect the author’s hypothesis on the emotional response pathways relating to the elicitation of stress with a required speech content. Finally the author provides guidelines and recommendations for future research on speech under stress. Further research paths are identified and a roadmap for future research in this area is defined.

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Sinapic acid (SA) is a nutraceutical with known anti-oxidant, anti-microbial, anti-inflammatory, anti-cancer, and anti-anxiety properties. Novel co-crystals of SA were prepared with co-formers belonging to the category of GRAS [isonicotinic acid (INC), nicotinamide (NIA)], non-GRAS [4-pyridinecarbonitrile (PYC)], and active pharmaceutical ingredients (APIs) [6-propyl-2-thiouracil (PTU)] list of compounds. Structural study based on the X-ray crystal structures revealed the intermolecular hydrogen-bonded interactions and molecular packing. The crystal structure of sinapic acid shows the anticipated acid-acid homodimer along with discrete hydrogen bonds between the acid carbonyl and the phenolic moiety. The robust acid-acid homodimer appears to be very stable and is retained in the structures of two co-crystals (SA[middle dot]NIA and SA[middle dot]PYC). In these cases, co-crystallization occurs via intermolecular phenol O-H[three dots, centered]Naromatic hydrogen bonds between the co-formers. In the SA[middle dot]PTU[middle dot]2MeCN co-crystal the acid-acid homodimer gives way to the anticipated acid-amide heterodimer, with the phenolic moiety of SA hydrogen-bonded to acetonitrile. Attempts at obtaining the desolvated co-crystal led to lattice breakdown, thus highlighting the importance of acetonitrile in the formation of the co-crystal. Among the co-crystals examined, SA[middle dot]INC (5 weeks), SA[middle dot]NIA (8 weeks) and SA[middle dot]PYC (5 weeks) were found to be stable under accelerated humidity conditions (40 [degree]C, 75% RH), whereas SA[middle dot]PTU[middle dot]2MeCN decomposed after one week into individual components due to solvent loss.