Abstract not found

Abstract not found

Content processing is a vast and growing field that integrates different approaches borrowed from the signal processing, information retrieval and machine learning disciplines. In this article we deal with a particular type of content processing: the so-called content-based transformations. We will not focus on any particular application but rather try to give an overview of different techniques and conceptual implications. We first describe the transformation process itself, including the main model schemes that are commonly used, which lead to the establishment of the formal basis for a definition of content-based transformations. Then we take a quick look at a general spectral based analysis/synthesis approach to process audio signals and how to extract features that can be used in the content-based transformation context. Using this analysis/synthesis approach we give some examples on how content-based transformations can be applied to modify the basic perceptual axis of a sound and how we can even combine different basic effects in order to perform more meaningful transformations. We finish by going a step further in the abstraction ladder and present transformations that are related to musical (and thus symbolic) properties rather than to those of the sound or the signal itself.

This article describes a collaborative project between researchers in the Mathematics and Computer Science Division at Argonne National Laboratory and the Computer Music Project of the University of Illinois at UrbanaChampaign. The project focuses on the use of sound for the exploration and analysis of complex data sets in scientific computing. The article addresses digital sound synthesis in the context of DIASS, a Digital Instrument for Additive Sound Synthesis, and sound visualization in a virtual-reality environment by means of M4CAVE. It describes the procedures and preliminary results of some experiments in scientific sonification and sound visualization. While most computational scientists routinely use visual imaging techniques to explore and analyze large data sets, they tend to be much less familiar with the use of sound. Yet, sound signals carry significant amounts of information and can be used advantageously to increase the bandwidth of the human/computer interface. The pr...

Interactive visualisation methods have been used to understand realtime acoustic analysis for the purpose of learning musical skills. However, interactive sonification has not often been considered, perhaps because it is assumed the musician cannot concentrate simultaneously on two sounds – their instrument’s sound, and the sonified information. However, whilst some finesse is required in designing sonification algorithms so that they interact with the musician’s sound in a controlled manner, there possibly are particular advantages to adopting the sonification approach. This research reports on a suite of interactive sonification algorithms for communicating real-time acoustic analysis results to singers and instrumentalists.

Our research considers the following question: how can visual, audio and tactile feedback be combined in a congruent manner for use with touchscreen graphical widgets? For example, if a touchscreen display presents different styles of visual buttons, what should each of those buttons feel and sound like? This paper presents the results of an experiment conducted to investigate methods of congruently combining visual and combined audio/tactile feedback by manipulating the different parameters of each modality. The results indicate trends with individual visual parameters such as shape, size and height being combined congruently with audio/tactile parameters such as texture, duration and different actuator technologies. We draw further on the experiment results using individual quality ratings to evaluate the perceived quality of our touchscreen buttons then reveal a correlation between perceived quality and crossmodal congruence. The results of this research will enable mobile touchscreen UI designers to create realistic, congruent buttons by selecting the most appropriate audio and tactile counterparts of visual button styles.

Can one trust experiments conducted with repetitive speech to represent normal language behaviour? We compare the spectra of repetitive productions of phrases with the same phrases read from a randomised list. We use a data-driven spectral distortion measure that is trained to respond to linguistically relevant differences: it is based on a classifier that separates sounds into linguistically equivalent or not. We find that repetitive speech is not distinct from individually uttered speech. The difference between these two sorts of speech is smaller than variation within each. It is substantially smaller than typical differences between utterances produced by different subjects.

In order to enable the user of a virtual reality system to be fully immersed in the virtual environment, the user must be presented with believable sensory input. Although the majority of virtual environments place the emphasis on visual cues, replicating the complex interactions of sound within an environment will benefit the level of immersion and hence the user's sense of presence. Three dimensional (spatial) sound systems allow a listener to perceive the position of sound sources, and the e#ect of the interaction of sound sources with the acoustic structure of the environment. This paper reviews the relevant biological and technical literature relevant to the generation of accurate acoustic displays for virtual environments, beginning with an introduction to the process of auditory perception in humans. This paper then critically examines common methods and techniques that have been used in the past as well as methods and techniques which are currently being used to generate spatial sound. In the process of doing so, the limitations, drawbacks, advantages and disadvantages associated with these techniques are also presented.

While environmental issues keep gaining increasing attention from the public opinion and policy makers, several experiments demonstrated the feasibility of wireless sensor networks to be used in a large variety of environmental monitoring applications. Focusing on the assessment of environmental noise pollution in urban areas, we provide qualitative considerations and preliminary experimental results that motivate and encourage the use of wireless sensor networks in this context.

Dissertation submitted to the University of Cambridge for the degree of Doctor of Philosophy Although the performance of speech recognition systems has increased substantially over the last decades, there still remain a number of tasks which pose considerable problems for current state-of-the-art techniques. One of these tasks is the recognition of spontaneous speech which differs from read or planned speech in that its underlying dynamics change frequently over time. The negative effect of changes in acoustic background condition on recognition performance can also be observed in other situations as, for instance, in the case of speech that is corrupted by non-stationary noise. This thesis is concerned with the development of an acoustic model for speech recognition which automatically detects changes in the background condition of a signal and compensates for the model-data mismatch by combining the information of several expert models. These experts are specialised on the different acoustic conditions under consideration and their influ-ence on the recognition process is determined by how well their associated condition matches