An important priority for the English Profile programme is to incorporate empirical evidence of the spoken language into the Common European Framework (CEFR). At present, the CEFR descriptors relating to the spoken language include references to fluency and its development as the learner moves from one level to another. This article offers a critique of the monologic bias of much of our current approach to spoken fluency. Fluency undoubtedly involves a degree of automaticity and the ability quickly to retrieve ready-made chunks of language. However, fluency also involves the ability to create flow and smoothness across turn-boundaries and can be seen as an interactive phenomenon in discourse. The article offers corpus evidence for the notion of confluence, that is the joint production of flow by more than one speaker, focusing in particular on turn-openings and closings. It considers the implications of an interactive view of fluency for pedagogy, assessment and in the broader social context.

This article investigates whether authentic native speaker (NS) to NS speech can be made available to the learner listener through the use of a novel slow-down tool. Results from various preliminary tests seem to indicate that the use of a slow-down algorithm in many cases, and in particular in samples with a higher speed rate and word count, leads to an improvement in subjects’ ability to perceive and understand what was being uttered in the samples. Tests revealed that even NS listeners, as opposed to non-native (NN) listeners, prefer to hear authentic NS speech which is either unscripted or is influenced by regional accent, at a slowed down speed. It also seems that ‘unexpected’ words (such as words with high contextual value, but which cannot be processed in a top-down fashion because of the size of the sound snippet) are initially not understood at the original speed of delivery, even in a scripted and carefully pronounced pedagogic sample. Samples containing chunks or formulaic sequences, however, appear to be easily understood at 100% by the majority of NS listeners due to the holistic processing of these language units.