New pinene-derived pyridines as bidentate chiral ligands

A synthesis of new bidentate pyridines has been developed, starting from ?-pinene. A copper complex of the pyridine-oxazoline ligands catalyzes asym. allylic oxidn. of cyclic olefins with good conversion rates and acceptable enantioselectivity (?67% ee). The imidazolium salt I has been identified as a precursor of the N,N'-unsym. N-heterocyclic carbene ligand, which upon complexation with palladium, catalyzed the intramol. amide enolate ?-arylation leading to oxindole in excellent yield but with low enantioselectivity.

Functionalised ionic liquids: synthesis of ionic liquids with tethered basic groups and their use in Heck and Knoevenagel reactions

A simple and efficient synthesis of a novel series of ionic liquids bearing nucleophilic (Me2N) and non-nucleophilic base ((Pr2N)-Pr-i) functionalities is described. The non-nucleophilic base functionality resembles the structure of the Hunig's base (N, N-diisopropylethylamine), which has been used widely in organic synthesis. A qualitative measure of the basicity of these ionic liquids is presented by utilising their interaction with universal indicator. The basicity of these ionic liquids was found to be dependent on the amine tether and choice of linker between the two nitrogen centres. The relative base strength of these ionic liquids was also probed by using them as catalysts in the Heck and Knoevenagel reactions.

Feature Selection for Pose Invariant Lip Biometrics

For the first time in this paper the authors present results showing the effect of out of plane speaker head pose variation on a lip biometric based speaker verification system. Using appearance DCT based features, they adopt a Mutual Information analysis technique to highlight the class discriminant DCT components most robust to changes in out of plane pose. Experiments are conducted using the initial phase of a new multi view Audio-Visual database designed for research and development of pose-invariant speech and speaker recognition. They show that verification performance can be improved by substituting higher order horizontal DCT components for vertical, particularly in the case of a train/test pose angle mismatch.

Inter-Frame Contextual Modelling For Visual Speech Recognition

In this paper, we present a new approach to visual speech recognition which improves contextual modelling by combining Inter-Frame Dependent and Hidden Markov Models. This approach captures contextual information in visual speech that may be lost using a Hidden Markov Model alone. We apply contextual modelling to a large speaker independent isolated digit recognition task, and compare our approach to two commonly adopted feature based techniques for incorporating speech dynamics. Results are presented from baseline feature based systems and the combined modelling technique. We illustrate that both of these techniques achieve similar levels of performance when used independently. However significant improvements in performance can be achieved through a combination of the two. In particular we report an improvement in excess of 17% relative Word Error Rate in comparison to our best baseline system.