This paper explores the problems of speech recognition in a (sometimes) noisy environment. An adaptive acoustic beamformer is proposed based on the Griffiths-Jim method and a 'hot-spot' where speech can be received within a geometric-defined boundary and rejected outside of it will be shown to give a certain amount of noise immunity and improve the signal-to-noise ratio for the second stage, which is the speech recognition engine. The recognition engine used has a limited vocabulary which gives rise to an excellent hit-rate and less training than unlimited vocabulary. The technology here has improved vastly within the last decade and it will be shown that by using a head and shoulders avatar that is both photo-realistic and with appealing personality, the experience of a speech interface is vastly enhanced. The paper will explore these technologies and investigate the convergence of many of them in the current Massey smart-office.