Separating and recognising speech in natural environments

In this challenge we consider the problem of separating and recognising speech in the cluttered acoustic backgrounds that characterise everyday listening conditions. In 2005, Pascal sponsored a highly successful ‘Speech Separation Challenge,’ which addressed the problem of recognising overlapping speech in single and multiple microphone scenarios. Although the challenge attracted much interest and culminated in the publication of a dedicated special issue of Computer Speech and Language, the focus on overlapping speech encouraged special-case solutions that do not necessarily generalise to real application scenarios. Five years on, the second challenge in PASCAL2 built on this work by extending the problem in ways that better modelled the demands of real noise-robust speech processing systems. In particular we considered the problem of a ‘speech-driven home automation’ application that needs to recognise spoken commands within the ongoing complex mixture of background sounds found in a typical domestic environment. The task was to identify the target commands being spoken given the binaural mixtures. Data was supplied first as isolated utterances (as is traditional for speech recognition evaluations) and then, more realistically, as sequences of utterances mixed intermittently into extended background recording sessions.