As the emphasis in cellular networks changes from voice-only communication to a rich combination of content based applications and services, speech recognition can provide access to several types of information through a number of portable solutions, including mobile phones and personal digital assistants.
Voicemail is a common part of any office solution today.
Sophisticated personal voicemail systems for the small office can be built using low cost computers and modern voiceband modems. The motivation lies on the fact that such systems can reduce delays to important decision-making as they are suitable for capturing and distributing information quickly, no matter ones location and without human intervention. Our approach to automatic summarization of voicemail has been extended by relating the prosodic features present in a message to the content of that message. We use Parcel feature subset selection algorithm to evaluate which of the several and often correlated lexical and prosodic features are potentially optimal as classifier inputs for voicemail summarization. Parcel minimizes the management of classifier performance data, facilitates the comparison of a large number of classifiers, and allows clear visual comparisons and sensitivity analysis.