Speech Perception in Virtual Environments

Many virtual environments like interactive computer games, educational software or training simulations make use of speech to convey important information to the user. These applications typically present a combination of background music, sound effects, ambient sounds and dialog simultaneously to create a rich auditory environment. Since interactive virtual environments allow users to roam freely among different sound producing objects, sound designers do not always have exact control over what sounds a user will perceive at any given time. This dissertation investigates factors that influence the perception of speech in virtual environments under adverse listening conditions. A virtual environment was created to study hearing performance under different audio-visual conditions. The two main areas of investigation were the contribution of "spatial unmasking" and lip animation to speech perception. Spatial unmasking refers to the hearing benefit achieved when the target sound and masking sound are presented from different locations. Both auditory and visual factors influencing speech perception were considered. The capability of modern sound hardware to produce a spatial release from masking using real-time 3D sound spatialization was compared with the pre-computed method of creating spatialized sound. It was found that spatial unmasking could be achieved when using a modern consumer 3D sound card and either a headphone or surround sound speaker display. Surprisingly, masking was less effective when using real-time sound spatialization and subjects achieved better hearing performance than when the pre-computed method was used. Most research on the spatial unmasking of speech has been conducted in pure auditory environments. The influence of an additional visual cue was first investigated to determine whether this provided any benefit. No difference in hearing performance was observed when visible objects were presented at the same location as the auditory stimuli. Because of inherent limitations of display devices, the auditory and visual environments are often not perfectly aligned, causing a sound-producing object to be seen at a different location from where it is heard. The influence of audio-visual integration between the conflicting spatial information was investigated to see whether it had any influence on the spatial unmasking of speech in noise. No significant difference in speech perception was found regardless of whether visual stimuli was presented at the correct location matching the auditory position, at a spatially disparate location from the auditory source. Lastly the influence of rudimentary lip animation on speech perception was investigated. The results showed that correct lip animations significantly contribute to speech perception. It was also found that incorrect lip animation could result in worse performance than when no lip animation is used at all. The main conclusions from this research are: That the 3D sound capabilities of modern sound hardware can and should be used in virtual environments to present speech; Perfectly align auditory and visual environments are not very important for speech perception; Even rudimentary lip animation can enhance speech perception in virtual environments

The influence of lip animation on the perception of speech in virtual environments

The addition of facial animation to characters greatly contributes to realism and presence in virtual environments. Even simple animations can make a character seem more lifelike and more believable. The purpose of this study was to determine whether the rudimentary lip animations used in most virtual environments could influence the perception of speech. The results show that lip animation can indeed enhance speech perception if done correctly. Lip movement that does not correlate with the presented speech however resulted in worse performance in the presence of masking noise than when no lip animation was used at all

Large Scale and Streaming Time Series Segmentation and Piece-Wise Approximation Extended Version

Abstract Segmenting a time series or approximating it with piecewise linear function is often needed when handling data in the time domain to detect outliers, clean data, detect events and more. The data varies from ECG signals, traffic monitors to stock prices and sensor networks. Modern data-sets of this type are large and in many cases are infinite in the sense that the data is a stream rather than a finite sample. Therefore, in order to segment it, an algorithm has to scale gracefully with the size of the data. Dynamic Programming (DP) can find the optimal segmentation, however, the DP approach has a complexity of O T 2 thus cannot handle datasets with millions of elements, nor can it handle streaming data. Therefore, various heuristics are used in practice to handle the data. This study shows that if the approximation measure has an inverse triangle inequality property (ITIP), the solution of the dynamic program can be computed in linear time and streaming data can be handled too. The ITIP is shown to hold in many cases of interest. The speedup due to the new algorithms is evaluated on a variety of data-sets to be in the range of 8 − 8200x over the DP solution without sacrificing accuracy. Confidence intervals for segmentations are derived as well

ICE: Enabling Non-Experts to Build Models Interactively for Large-Scale Lopsided Problems

Quick interaction between a human teacher and a learning machine presents numerous benefits and challenges when working with web-scale data. The human teacher guides the machine towards accomplishing the task of interest. The learning machine leverages big data to find examples that maximize the training value of its interaction with the teacher. When the teacher is restricted to labeling examples selected by the machine, this problem is an instance of active learning. When the teacher can provide additional information to the machine (e.g., suggestions on what examples or predictive features should be used) as the learning task progresses, then the problem becomes one of interactive learning. To accommodate the two-way communication channel needed for efficient interactive learning, the teacher and the machine need an environment that supports an interaction language. The machine can access, process, and summarize more examples than the teacher can see in a lifetime. Based on the machine's output, the teacher can revise the definition of the task or make it more precise. Both the teacher and the machine continuously learn and benefit from the interaction. We have built a platform to (1) produce valuable and deployable models and (2) support research on both the machine learning and user interface challenges of the interactive learning problem. The platform relies on a dedicated, low-latency, distributed, in-memory architecture that allows us to construct web-scale learning machines with quick interaction speed. The purpose of this paper is to describe this architecture and demonstrate how it supports our research efforts. Preliminary results are presented as illustrations of the architecture but are not the primary focus of the paper

n Numeriese oplossing van 'n grondwatermodel op die Kaapse Vlakte met behulp van eindige elemente

Skripsie (M. Sc.) -- Universiteit van Stellenbosch, 1984.Full text to be digitised and attached to bibliographic record

Guidelines for heart transplantation

Based on the changes in the field of heart transplantation and the treatment and prognosis of patients with heart failure, these updated guidelines were composed by a committee under the supervision of both the Netherlands Society of Cardiology and the Netherlands Association for Cardiothoracic surgery (NVVC and NVT). The indication for heart transplantation is defined as: 'End-stage heart disease not remediable by more conservative measures'. Contraindications are: irreversible pulmonary hypertension/elevated pulmonary vascular resistance; active systemic infection; active malignancy or history of malignancy with probability of recurrence; inability to comply with complex medical regimen; severe peripheral or cerebrovascular disease and irreversible dysfunction of another organ, including diseases that may limit prognosis after heart transplantation. Considering the difficulties in defining end-stage heart failure, estimating prognosis in the individual patient and the continuing evolution of available therapies, the present criteria are broadly defined. The final acceptance is done by the transplant team which has extensive knowledge of the treatment of patients with advanced heart failure on the one hand and thorough experience with heart transplantation and mechanical circulatory support on the other hand