We present a sound synthesizer dedicated to particle-based environmental effects, for use in interactive virtual environments. The synthesis engine is based on five physically-inspired basic elements which we call sound atoms, that can be parameterized and stochastically distributed in time and space. Based on this set of atomic elements, models are presented for reproducing several environment...

This paper develops ideas on moving “soundscapes” into the mainstream of activity of environmental noise. Such a move has value in introducing a new dimension aimed at catching political attention and the engagement of other professions in acoustic management of outdoor environments. “Quiet Areas” the EU Directive on Environmental Noise requires “preserving environmental noise quality where it ...

This paper examines the concept of "quiet" as an "environmental value" in terms of amenity and wellbeing from a legislative context. Critical review of two pieces of environmental legislation from Australia and New Zealand forms the basis of the paper. The Australian legislation is Queensland's Environmental Protection Act, and the New Zealand legislation is that nation's Resource Management Ac...

Public participation within environmental monitoring may contribute to increasing the knowledge on the state of the environment at the same time it promotes citizens' involvement in environmental protection. However, the use of voluntary collected data is limited due to a lack of confidence in data collection procedures. Additionally, data quality is often unknown and the data are usually dispe...

In this paper, we propose a new framework for environmental sound synthesis using onomatopoeic words and event labels. The conventional method of synthesis, in which only labels are used, cannot finely control the time-frequency structural features synthesized sounds, such as duration, timbre, pitch. There various ways to express other than labels, use words. An word, is character sequence phon...

Our goal is to develop a system to learn and classify environmental sounds for robots working in the real world. In the real world, two main restrictions pertain in learning. First, robots have to learn using only a small amount of data in a limited time because of hardware restrictions. Second, it has to adapt to unknown data since it is virtually impossible to collect samples of all environme...