Abstract: An approach is provided in which an information handling system analyzes a set of historical form data corresponding to a set of completed forms. The set of historical form data includes information indicating a historical order at which a set of fields were completed in the set of completed forms. Next, the information handling system determines, based on the set of historical form data, a current order at which to complete a set of incomplete fields included in a current form. In turn, the information handling system displays the current form and a user interface on a display that indicates the current order at which to complete the incomplete fields on the current form.

Abstract: A prescriptive meeting resource recommendation engine automatically learns participant and resource preferences in the context of given meeting input data using natural language features, and automatically recommends all relevant participants and resources (teleconferences, web meetings, links, etc.) to the meeting creator. The engine uses a feature data store to associate historical persons and historical resources with various natural language features, e.g., chargrams. As the host enters text in an invitation template (such as in the title field), the engine extracts current natural language features and computes current participant scores and current resource scores based on the current natural language features. A “forgetfulness” routine is applied to the feature data store to phase out the influence of stale data.

Abstract: A method, system, and computer program product are provided for classifying spoken audio content with a cognitive audio classifier by applying a set of distorted audio resources through a set of speech-to-text models STTi (STT1 . . . STTn) to get a set of interference coherence scores based on the transcript for each speech-to-text model STTi, thereby generating a measured baseline Mi (M1 . . . Mn) and a practical baseline Pi (P1 . . . Pn) that is associated with a coherence matrix for the audio effects AEj (AE1 . . . AEk) that were used to generate the distorted audio resources, thereby generating training data for use in training a cognitive audio classifier which classifies input spoken audio content to measure a quality of detected vocabulary elements from the spoken audio content under the set of audio distortion effects for each speech-to-text model STTi.

Abstract: A system, computer program product, and method are provided to leverage a taxonomy service to format ground truth data. An artificial intelligence platform processes ground truth data, including identification of one or more applicable taxonomy tags. The identified tags are filtered and applied to the ground truth data, thereby constructing an output string that incorporates the ground truth data together with one or more of the identified tags, effectively transforming the ground truth data. Application of the transformed ground truth data is employed to accurately identify the source and/or meaning of the natural language, and in one embodiment, to produce a physical action or transformation of a physical hardware device.

Abstract: An approach is provided in which an information handling system analyzes a set of historical form data corresponding to a set of completed forms. The set of historical form data includes information indicating a historical order at which a set of fields were completed in the set of completed forms. Next, the information handling system determines, based on the set of historical form data, a current order at which to complete a set of incomplete fields included in a current form. In turn, the information handling system displays the current form and a user interface on a display that indicates the current order at which to complete the incomplete fields on the current form.

Abstract: A method, system, and computer program product are provided for classifying spoken audio content with a cognitive audio classifier by applying a set of distorted audio resources through a set of speech-to-text models STTi (STT1 . . . STTn) to get a set of interference coherence scores based on the transcript for each speech-to-text model STTi, thereby generating a measured baseline Mi (M1 . . . Mn) and a practical baseline Pi (P1 . . . Pn) that is associated with a coherence matrix for the audio effects AEj (AE1 . . . AEk) that were used to generate the distorted audio resources, thereby generating training data for use in training a cognitive audio classifier which classifies input spoken audio content to measure a quality of detected vocabulary elements from the spoken audio content under the set of audio distortion effects for each speech-to-text model STTi.

Abstract: A prescriptive meeting resource recommendation engine automatically learns participant and resource preferences in the context of given meeting input data using natural language features, and automatically recommends all relevant participants and resources (teleconferences, web meetings, links, etc.) to the meeting creator. The engine uses a feature data store to associate historical persons and historical resources with various natural language features, e.g., chargrams. As the host enters text in an invitation template (such as in the title field), the engine extracts current natural language features and computes current participant scores and current resource scores based on the current natural language features. A “forgetfulness” routine is applied to the feature data store to phase out the influence of stale data.

Abstract: A system, computer program product, and method are provided to leverage a taxonomy service to format ground truth data. An artificial intelligence platform processes ground truth data, including identification of one or more applicable taxonomy tags. The identified tags are filtered and applied to the ground truth data, thereby constructing an output string that incorporates the ground truth data together with one or more of the identified tags, effectively transforming the ground truth data. Application of the transformed ground truth data is employed to accurately identify the source and/or meaning of the natural language, and in one embodiment, to product a physical action or transformation of a physical hardware device.

Abstract: A system, computer program product, and method are provided to leverage a taxonomy service to format ground truth data. An artificial intelligence platform processes ground truth data, including identification of one or more applicable taxonomy tags. The identified tags are filtered and applied to the ground truth data, thereby constructing an output string that incorporates the ground truth data together with one or more of the identified tags, effectively transforming the ground truth data. Application of the transformed ground truth data is employed to accurately identify the source and/or meaning of the natural language, and in one embodiment, to product a physical action or transformation of a physical hardware device.

Abstract: A system, computer program product, and method are provided to leverage a taxonomy service to format ground truth data. An artificial intelligence platform processes ground truth data, including identification of one or more applicable taxonomy tags. The identified tags are filtered and applied to the ground truth data, thereby constructing an output string that incorporates the ground truth data together with one or more of the identified tags, effectively transforming the ground truth data. Application of the transformed ground truth data is employed to accurately identify the source and/or meaning of the natural language, and in one embodiment, to product a physical action or transformation of a physical hardware device.

Abstract: In an approach for providing a recommendation for human interaction in an environment, a processor receives information from one or more devices in an area. A processor analyzes the information to identify at least two people and a context of an interaction, wherein a first person has the interaction with a second person. A processor applies a behavioral model to the context and the interaction to identify a recommendation, wherein the behavioral model is a model of a plurality of previous interactions in a plurality of areas, a plurality of contexts associated to the plurality of previous interactions, and a plurality of recommendations associated to the plurality of previous interactions. A processor provides the recommendation to the first person.