Modeling the development of pronunciation in infant speech acquisition.

Pronunciation is an important part of speech acquisition, but little attention has been given to the mechanism or mechanisms by which it develops. Speech sound qualities, for example, have just been assumed to develop by simple imitation. In most accounts this is then assumed to be by acoustic matching, with the infant comparing his output to that of his caregiver. There are theoretical and empirical problems with both of these assumptions, and we present a computational model- Elija-that does not learn to pronounce speech sounds this way. Elija starts by exploring the sound making capabilities of his vocal apparatus. Then he uses the natural responses he gets from a caregiver to learn equivalence relations between his vocal actions and his caregiver's speech. We show that Elija progresses from a babbling stage to learning the names of objects. This demonstrates the viability of a non-imitative mechanism in learning to pronounce.

KLAIR: A virtual infant for spoken language acquisition research

Recent research into the acquisition of spoken language has stressed the importance of learning through embodied linguistic interaction with caregivers rather than through passive observation. However the necessity of interaction makes experimental work into the simulation of infant speech acquisition difficult because of the technical complexity of building real-time embodied systems. In this paper we present KLAIR: a software toolkit for building simulations of spoken language acquisition through interactions with a virtual infant. The main part of KLAIR is a sensori-motor server that supplies a client machine learning application with a virtual infant on screen that can see, hear and speak. By encapsulating the real-time complexities of audio and video processing within a server that will run on a modern PC, we hope that KLAIR will encourage and facilitate more experimental research into spoken language acquisition through interaction. Copyright © 2009 ISCA.

Soil mix technology for land remediation: Recent innovations

The past 15 years have seen increasing applications of soil mix technology in land remediation, mainly in stabilisation/solidification treatments and the construction of low-permeability cut-off walls and permeable reactive barriers; clear evidence of the versatility of the technology and its wide-ranging applications. This paper provides an overview of some of the recent innovations of soil mix technology in land remediation covering equipment developments and applications, including systems for rectangular panels and trenching systems, treatments, such as chemical oxidation, and additives, such as modified clays, zeolites and reactive magnesia. The paper also provides case studies for such innovations. The paper concludes with an overview of an on-going research and development project SMiRT (Soil Mix Remediation Technology) which will involve field trials on a contaminated site and will employ some of the innovations discussed in the paper. The range of significant advantages that soil mix technology now offers compared to other remediation techniques is likely to place this remediation method at the forefront of remedial options for future brownfield projects.