The effect of prior visual information on recognition of speech and sounds

To identify and categorize complex stimuli such as familiar objects or speech, the human brain integrates information that is abstracted at multiple levels from its sensory inputs. Using cross-modal priming for spoken words and sounds, this functional magnetic resonance imaging study identified 3 distinct classes of visuoauditory incongruency effects: visuoauditory incongruency effects were selective for 1) spoken words in the left superior temporal sulcus (STS), 2) environmental sounds in the left angular gyrus (AG), and 3) both words and sounds in the lateral and medial prefrontal cortices (IFS/mPFC). From a cognitive perspective, these incongruency effects suggest that prior visual information influences the neural processes underlying speech and sound recognition at multiple levels, with the STS being involved in phonological, AG in semantic, and mPFC/IFS in higher conceptual processing. In terms of neural mechanisms, effective connectivity analyses (dynamic causal modeling) suggest that these incongruency effects may emerge via greater bottom-up effects from early auditory regions to intermediate multisensory integration areas (i.e., STS and AG). This is consistent with a predictive coding perspective on hierarchical Bayesian inference in the cortex where the domain of the prediction error (phonological vs. semantic) determines its regional expression (middle temporal gyrus/STS vs. AG/intraparietal sulcus).

A Likelihood-Maximizing Framework for Enhanced In-Car Speech Recognition Based on Speech Dialog System Interaction

Speech recognition in car environments has been identified as a valuable means for reducing driver distraction when operating noncritical in-car systems. Under such conditions, however, speech recognition accuracy degrades significantly, and techniques such as speech enhancement are required to improve these accuracies. Likelihood-maximizing (LIMA) frameworks optimize speech enhancement algorithms based on recognized state sequences rather than traditional signal-level criteria such as maximizing signal-to-noise ratio. LIMA frameworks typically require calibration utterances to generate optimized enhancement parameters that are used for all subsequent utterances. Under such a scheme, suboptimal recognition performance occurs in noise conditions that are significantly different from that present during the calibration session – a serious problem in rapidly changing noise environments out on the open road. In this chapter, we propose a dialog-based design that allows regular optimization iterations in order to track the ever-changing noise conditions. Experiments using Mel-filterbank noise subtraction (MFNS) are performed to determine the optimization requirements for vehicular environments and show that minimal optimization is required to improve speech recognition, avoid over-optimization, and ultimately assist with semireal-time operation. It is also shown that the proposed design is able to provide improved recognition performance over frameworks incorporating a calibration session only.

Estimating link-dependent origin-destination matrices from sample trajectories and traffic counts

In transport networks, Origin-Destination matrices (ODM) are classically estimated from road traffic counts whereas recent technologies grant also access to sample car trajectories. One example is the deployment in cities of Bluetooth scanners that measure the trajectories of Bluetooth equipped cars. Exploiting such sample trajectory information, the classical ODM estimation problem is here extended into a link-dependent ODM (LODM) one. This much larger size estimation problem is formulated here in a variational form as an inverse problem. We develop a convex optimization resolution algorithm that incorporates network constraints. We study the result of the proposed algorithm on simulated network traffic.

Using smartphones for cycling safety: A survey of riders preferences and interest in new technologies

Cyclists are among the most vulnerable road users. Many recent interventions have aimed at improving their safety on the road, such as the minimum overtaking distance rule introduced in Queensland in 2014. Smartphones offer excellent opportunities for technical intervention for road safety at a limited cost. Indeed, they have a lot of available processing power and many embedded sensors that allow analysing a rider's (or driver's) motion, behaviour, and environment; this is especially relevant for cyclists, as they do not have the space or power allowance that can be found in most motor vehicles. The aim of the study presented in this paper is to assess cyclists’ support for a range of new smartphone-based safety technologies. The preliminary results for an online survey with cyclists recruited from Bicycle Queensland and Triathlon Queensland, with N=191, are presented. A number of innovative safety systems such as automatic logging of incidents without injuries, reporting of dangerous area via a website/app, automatic notification of emergency services in case of crash or fall, and advanced navigation apps were assessed. A significant part of the survey is dedicated to GoSafeCycle, a cooperative collision prevention app based on motion tracking and Wi-Fi communications developed at CARRS-Q. Results show a marked preference toward automatic detection and notification of emergencies (62-70% positive assessment) and GoSafeCycle (61.7% positive assessment), as well as reporting apps (59.1% positive assessment). Such findings are important in the context of current promotion of active transports and highlight the need for further development of system supported by the general public.

Experimental studies on comparison of microwave curing and thermal curing of epoxy resins used for alternative mould materials

In this present work attempts have been made to study the glass transition temperature of alternative mould materials by using both microwave heating and conventional oven heating. In this present work three epoxy resins, namely R2512, R2515 and R2516, which are commonly used for making injection moulds have been used in combination with two hardeners H2403 and H2409. The magnetron microwave generator used in this research is operating at a frequency of 2.45 GHz with a hollow rectangular waveguide. In order to distinguish the effects between the microwave and conventional heating, a number of experiments were performed to test their mechanical properties such as tensile and flexural strengths. Additionally, differential scanning calorimeter technique was implemented to measure the glass transition temperature on both microwave and conventional heating. This study provided necessary evidences to establish that microwave heated mould materials resulted with higher glass transition temperature than the conventional heating. Finally, attempts were also made to study the microstructure of microwave-cured materials by using a scanning electron microscope in order to analyze the morphology of cured specimens.