International Business Machines Corporation

Sara H Waggoner

Kaleb Dean Walton

Aaron T Wodrich

Patrick A Spizzo

Rhonda L Childress

Ravi Prakash Bansal

Ravirajan Rajan

Michael B Oliver

Kenneth M Becker

Brent W Lamm

Timothy J Carroll

Saravanan Kannappan

Robert J Carney

Thomas L Newton

In an approach to determining speech effectiveness, one or more computer processors receive speech input. The one or more computer processors determine, based, at least in part, on the received speech input, a first speaking mode. The one or more computer processors detect, based, at least in part, on the first speaking mode, at least one aspect of the received speech input. The one or more computer processors determine, based, at least in part, on the first speaking mode and the detected at least one aspect of the received speech input, whether a rate of occurrence of the detected at least one aspect of the speech input exceeds a pre-defined threshold. Responsive to determining a rate of occurrence of the detected at least one aspect of the speech input exceeds a pre-defined threshold, the one or more computer processors notify a user.

Rating speech effectiveness based on speaking mode

In an approach to determining speech effectiveness, a computer receives speech input. The computer determines, based, at least in part, on the received speech input, whether the speech input is one of: a conversation with words spoken by two or more people during a predetermined time interval, and a presentation with words spoken by one person and not any other person during a predetermined time interval. The computer detects at least one problem with the speech input. If the speech input is the presentation, the computer weights, by a first factor, the detected at least one problem with the speech input based on the speech input being a presentation and not a conversation, and if the speech input is a conversation, the computer weights, by a second factor, the detected at least one problem with the speech input based on the speech input being a conversation and not a presentation.

Speech effectiveness rating

A meta object facility file is parsed into a plurality of schema elements. For each schema element, it is determined that the definition of the schema element is complete. A computing artifact usable in a database description language database table or a Jclass is created from the schema element. When the schema element is a meta object facility class, a modeling entity is created to store the computing artifacts derived from the meta object facility file wherein the modeling entity is a Jclass. The meta object facility class is transformed into a Jclass, and upon determining that an attribute of the meta object facility class has an array of values, an array table is created and identified in the modeling entity, and an array attribute is added to Jinformation in the modeling entity.

transforming meta object facility specifications into relational data definition language structures and JAVA classes

Disclosed are a tool, a method, and a computer program for suppressing events. The tool comprises a database having a resource table, a batch loader interface for creating or updating said resource table, and a web based user interface to said database. The event suppression tool further comprises a batch interface to receive data about planned activities and affected resources; and code for creating suppression activity windows from said data and said resource table, and for suppressing from said user interface, new events that fall within said activity windows. The preferred embodiment of the invention allows temporarily suppressing various actions for events received for certain resources during specified times.

Event suppression tool for temporarily suppressing actions on received events

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Bradenton, FL, United States of America

Sara H Waggoner