Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: obtaining the media file with a speech and identifying speakers on clusters separated by disfluencies and change of speakers. Clusters are re-segmented rearranged during diarization. Speaker identifications for the clusters in the media file is produced.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: obtaining the media file with a speech and identifying speakers on clusters separated by disfluencies and change of speakers. Clusters are re-segmented rearranged during diarization. Speaker identifications for the clusters in the media file is produced.

Abstract: Using a simple cue to reduce a number of sequential frames included in a video that needs to be analyzed by an artificial neural network to predict information corresponding to a projectile depicted within the video is provided. A timing of the simple cue associated with the video is detected. The number of sequential frames within the video is reduced down to only those frames that are within a specified range of the simple cue. The artificial neural network is used to analyze the reduced number of sequential frames. The information corresponding to the projectile is predicted based on analyzing the reduced number of sequential frames using the artificial neural network.

Abstract: A computer-implemented method includes monitoring, by a computing device, sensor data during gameplay of a sporting event; determining, by the computing device, predictive factors associated with a target based on the monitoring the sensor data; determining, by the computing device, a real-time region of effectiveness for the target based on the predictive factors and training data identifying historical effectiveness of the target; and outputting, by the computing device, the real-time region of effectiveness for displaying the real-time region of effectiveness around the target.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: obtaining a media file including a speech by one or more speaker. The language of the speech is identified and biographic data of a speaker of the speech is generated by analyzing semantics and vocal characteristics of the speech. The speaker is diarized and confidence in a resulting speaker label is evaluated against a threshold. The speaker label is adjusted with the language of the speech and biographic data of the speaker and produced as speaker metadata of the media file.

Abstract: A reflection is captured of a subsonic signal reflected by a contact surface. The contact surface is contacting a simulated surface of an object projected from a midair interface (MAI) device. A difference between the subsonic signal and the reflection is converted into a measurement of a flow in the contact surface. When the measurement is in a range of measurements, a change is caused in a temperature of a volume of a medium, the simulated surface being projected in volume of the medium, where the change in the temperature causes a second change in the flow in the contact surface.

Abstract: Aspects of the present invention provide devices that subtitle streaming video with audio and identify a speaker in a streaming video with audio according to words spoken by the speaker matched to a cognitive print. The cognitive print includes traits classified according a hierarchical long short term model (LSTM). The hierarchical LSTM includes layers of LSTMs and each layer corresponds to the classification of one trait. A processor annotates a subtitle of the words spoken by the speaker, which decorates the subtitle with a label representative of the identified speaker, and streams the decorated subtitle with the streaming video with audio.

Abstract: Systems and methods for customizing digital content based on consumer context data are disclosed. In embodiments, a computer-implemented method, comprises: determining, by a computing device, a goodness of fit of one or more digital content segments for a digital product based on asset success metrics indicating a trend in consumer consumption of content; identifying, by the computing device, a select digital content segment from the one or more digital content segments based on the goodness of fit; and incorporating, by the computing device, the select digital content segment into the digital product.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: obtaining a media file including a speech by one or more speaker. The language of the speech is identified and biographic data of a speaker of the speech is generated by analyzing semantics and vocal characteristics of the speech. The speaker is diarized and confidence in a resulting speaker label is evaluated against a threshold. The speaker label is adjusted with the language of the speech and biographic data of the speaker and produced as speaker metadata of the media file.

Abstract: Devices and methods for modeling streaming data are disclosed. A method includes: receiving, by a computing device, a local graph model; determining, by the computing device, a subgraph in the local graph model; acquiring, by the computing device, an external graph model; determining, by the computing device, a plurality of alternative subgraphs in the external graph model; determining, by the computing device, a score for each of the plurality of alternative subgraphs; selecting, by the computing device, an alternative subgraph having a highest score among the plurality of alternative subgraphs; and ensembling, by the computing device, the local graph model and the alternative subgraph having the highest score.

Abstract: A method and system for auto-curating a media are provided. Media content is received over the network interface. A set of markers is identified for the media content, each marker corresponding to one of a plurality of visible and audible cues in the media content. Segments in the media content are identified based on the identified set of markers. An excitement score is computed for each segment based on the identified markers that fall within the segment. A highlight clip is generated by identifying segments having excitement scores greater than a threshold.

Abstract: Simulating uncertainty in an artificial neural network is provided. Aleatoric uncertainty is simulated to measure what the artificial neural network does not understand from sensor data received from an object operating in a real-world environment by adding random values to edge weights between nodes in the artificial neural network during backpropagation of output data of the artificial neural network and measuring impact on the output data by the added random values to the edge weights between the nodes. Epistemic uncertainty is simulated to measure what the artificial neural network does not know by dropping out a selected node from each respective layer of the artificial neural network during forward propagation of the sensor data and measuring impact of dropped out nodes on the output data of the artificial neural network. An action corresponding to the object is performed based on the impact of simulating the aleatoric and epistemic uncertainty.

Abstract: Focus data of a remote user is analyzed to determine a focus shift from a first area to a second area at an event arena. A beacon density is computed at the second area, where the beacon density includes a number of physical beacons corresponding to a number of local users at the second area, a number of virtual beacons corresponding to a number of remote users focused on the second area, or a combination of thereof. When the beacon density at the second area exceeds a threshold density, an instruction to a streaming source is generated. The streaming source is caused to change a streaming content, to form changed streaming content that is related to the second area.

Abstract: A method, system and computer program product for the contextualized weather summarization for a target event includes the receipt in memory of a computer of a weather report corresponding to a geographical locale corresponding to a particular event and venue for the event and the processing of the received weather report to generate a multiplicity of different contextual summarizations utilizing a pre-established weather grammar. Then, a processor of the computer analyzes each one of the different contextual summarizations to measure a tone ranging from negative to positive. Finally, the processor transmits a most positive measured one of the contextual summarizations over the computer communications network to end users seeking a weather forecast for the geographical locale corresponding to the particular event and venue for the event.

Abstract: Focus data of a remote user is analyzed to determine a focus shift from a first area to a second area at an event arena. A beacon density is computed at the second area, where the beacon density includes a number of physical beacons corresponding to a number of local users at the second area, a number of virtual beacons corresponding to a number of remote users focused on the second area, or a combination of thereof. When the beacon density at the second area exceeds a threshold density, an instruction to a streaming source is generated. The streaming source is caused to change a streaming content, to form changed streaming content that is related to the second area.

Abstract: In an approach for acoustic modeling with a language model, a computer isolates an audio stream. The computer identifies one or more language models based at least in part on the isolated audio stream. The computer selects a language model from the identified one or more language models. The computer creates a text based on the selected language model and the isolated audio stream. The computer creates an acoustic model based on the created text. The computer generates a confidence level associated with the created acoustic model. The computer selects a highest ranked language model based at least in part on the generated confidence level.

Abstract: A processor may monitor frequency data related to a user metric of a user during a measurement window. The user metric may relate to the user's use of a computer implemented environment. The processor may simplify the frequency data related to the user metric, resulting in a set of simplified frequency data. The processor may input the set of simplified frequency data into a neural network. The neural network may determine a likelihood of a negative user experience for the user. The processor may alter a parameter of the first user environment based on the likelihood.

Abstract: In an approach for acoustic modeling with a language model, a computer isolates an audio stream. The computer identifies one or more language models based at least in part on the isolated audio stream. The computer selects a language model from the identified one or more language models. The computer creates a text based on the selected language model and the isolated audio stream. The computer creates an acoustic model based on the created text. The computer generates a confidence level associated with the created acoustic model. The computer selects a highest ranked language model based at least in part on the generated confidence level.

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: running a comment examining process for processing comments of one or more user to provide a comment processing output; applying data of a dataset as training data for training a neural network to define a trained neural network, wherein the training data includes input node training data and output node training data; and generating a decision rule for the dataset based on a transfer function of the trained neural network, wherein the decision rule is based on the comment processing output.

Abstract: A hierarchy of agents is constructed from a set of agents. Each agent in the hierarchy is trained to answer a question according to a corresponding corpus associated with the agent, which contains a portion of knowledge about a subject-matter. The question is submitted to a first subset of agents, the agents in the first subset occupying a first level in the hierarchy. From a first agent in the first subset, a first answer is propagated to a second agent in a second subset of agents, the first agent computing the first answer using a first portion of knowledge about the subject-matter. to form a first morphed answer, a second answer is added to the first answer, the second answer being computed by the second agent using a second portion of knowledge about the subject-matter. The morphed answer is produced in response to the question.