Practical issues in the application of speech technology to network and customer service applications

Abstract

This paper proposes a simple model to characterise the different stages of short telephone transactions. It also discusses the impact of the context of the caller when entering an automated service. Three different styles of service were then identified, namely, large vocabulary information gathering, spoken language command and natural language task identification for helpdesks. By considering human dialogue equivalents, the requirements for each style are considered. Consequently, it is shown that each style pushes different technological limits. Three case studies, selected from current project from BT laboratories, are presented to highlight the practical design issues in these different styles. The styles and case studies presented are: • Information gathering – UK name and address recognition. • Spoken language command – network service configuration. • Natural language helpdesks – BT operator services. It is shown that large vocabulary information gathering systems require high accuracy, careful data modelling and well-designed strategies to boost confidence and accuracy. Spoken language command requires dialogue and grammar design and test complexity to be managed. Natural language task identification requires large volumes of training data, good learning algorithms and good data generalisation techniques. These styles can be mixed into a single interaction meaning that design frameworks of the future will have to address all of the aspects of the different interaction styles.