Using SenseCam images in a multimodal fusion framework for route detection and localisation

Problem of structuring location data is solved by proposing a framework for classifying the data into often-traversed routes. It does not rely on any one source of location information, but can fuse data from multimodal localisation sources: SenseCam images, GPS data and WLAN signal strengths

Bioinspired auditory sound localisation for improving the signal to noise ratio of socially interactive robots

In this paper we describe a bioinspired hybrid architecture for acoustic sound source localisation and tracking to increase the signal to noise ratio (SNR) between speaker and background sources for a socially interactive robot's speech recogniser system. The model presented incorporates the use of Interaural Time Differ- ence for azimuth estimation and Recurrent Neural Net- works for trajectory prediction. The results are then pre- sented showing the difference in the SNR of a localised and non-localised speaker source, in addition to presenting the recognition rates between a localised and non-localised speaker source. From the results presented in this paper it can be seen that by orientating towards the sound source of interest the recognition rates of that source can be in- creased

Particle Filter Design Using Importance Sampling for Acoustic Source Localisation and Tracking in Reverberant Environments

Sequential Monte Carlo methods have been recently proposed to deal with the problem of acoustic source localisation and tracking using an array of microphones. Previous implementations make use of the basic bootstrap particle filter, whereas a more general approach involves the concept of importance sampling. In this paper, we develop a new particle filter for acoustic source localisation using importance sampling, and compare its tracking ability with that of a bootstrap algorithm proposed previously in the literature. Experimental results obtained with simulated reverberant samples and real audio recordings demonstrate that the new algorithm is more suitable for practical applications due to its reinitialisation capabilities, despite showing a slightly lower average tracking accuracy. A real-time implementation of the algorithm also shows that the proposed particle filter can reliably track a person talking in real reverberant rooms.This paper was performed while Eric A. Lehmann was working with National ICT Australia. National ICT Australia is funded by the Australian Government’s Department of Communications, Information Technology, and the Arts, the Australian Research Council, through Backing Australia’s Ability, and the ICT Centre of Excellence programs

Relative sound localisation abilities in human listeners

Spatial acuity varies with sound-source azimuth, signal-to-noise ratio, and the spectral characteristics of the sound source. Here, the spatial localisation abilities of listeners were assessed using a relative localisation task. This task tested localisation ability at fixed angular separations throughout space using a two-alternative forced-choice design across a variety of listening conditions. Subjects were required to determine whether a target sound originated to the left or right of a preceding reference in the presence of a multi-source noise background. Experiment 1 demonstrated that subjects' ability to determine the relative location of two sources declined with less favourable signal-to-noise ratios and at peripheral locations. Experiment 2 assessed performance with both broadband and spectrally restricted stimuli designed to limit localisation cues to predominantly interaural level differences or interaural timing differences (ITDs). Predictions generated from topographic, modified topographic, and two-channel models of sound localisation suggest that for low-pass stimuli, where ITD cues were dominant, the two-channel model provides an adequate description of the experimental data, whereas for broadband and high frequency bandpass stimuli none of the models was able to fully account for performance. Experiment 3 demonstrated that relative localisation performance was uninfluenced by shifts in gaze direction

Environment-assisted quantum transport in ordered systems

Noise-assisted transport in quantum systems occurs when quantum time-evolution and decoherence conspire to produce a transport efficiency that is higher than what would be seen in either the purely quantum or purely classical cases. In disordered systems, it has been understood as the suppression of coherent quantum localisation through noise, which brings detuned quantum levels into resonance and thus facilitates transport. We report several new mechanisms of environment-assisted transport in ordered systems, in which there is no localisation to overcome and where one would naively expect that coherent transport is the fastest possible. Although we are particularly motivated by the need to understand excitonic energy transfer in photosynthetic light-harvesting complexes, our model is general---transport in a tight-binding system with dephasing, a source, and a trap---and can be expected to have wider application