Intel Corporation

Guillermo Perez

Gabriel Amores

Israel Perez Tudela

Moshe Wasserblat

Michael E Deisher

Martin Henk Van Den Berg

Steven Thomas Holmes

Robert J Firby

Jesus Gonzalez Marti

Maria Pilar Manchon Portillo

Loic Dufresne De Virel

Jose Gabriel De Amores Carredano

Systems, apparatuses and methods may provide for technology to improve a workout experience of a user by determining an emotional state of the user, identifying a workout route based on the emotional state of the user, and outputting the workout route via a user interface device. Additionally, determining the emotional state of the user may include inferring emotions from one or more sensor information or user speech information. In one example, the sensor information includes one or more of blood pressure signals, heart rate signals or sweat measurement signals and the user speech information includes one or more of words used in an input utterance or a prosody of the input utterance.

Using emotional maps and dialog display technology to improve workout experiences

An apparatus for speech model with personalization via ambient context harvesting, is described herein. The apparatus includes a microphone, context harvesting module, confidence module, and training module. The context harvesting module is to determine a context associated with the captured audio signals. A confidence module is to determine a confidence of the context as applied to the audio signals. A training module is to train a neural network in response to the confidence being above a predetermined threshold.

Speech model personalization via ambient context harvesting

Particular embodiments described herein provide for an electronic device that can be configured to receive a verbal command to active a device with an unknown label, derive a probable device and a label for the probable device, activate the probable device, determine that the activated probable device is the same device to be activated by the verbal command, and store the label and a description for the device. In some examples, the label is associated with the description.

Device identification through dialog

Methods, systems and articles of manufacture for a communication system that allows a robot to interact with users via a single party dialogue strategy or a multi-party dialogue strategy are disclosed. An example communication system includes a distance tracker to determine whether any of a plurality of parties has come within a conversation distance of the communication system. The example communication system can also include a first dialogue handler in communication with a first memory storing a single party dialogue processing algorithm and a second dialogue handler in communication with a second memory storing a multi-party dialogue processing algorithm. Based on information supplied by the distance tracker, a dialogue mode selector selects between the first dialogue handler and the second dialogue handler to process conversations between the robot and a first party and the robot and a second party.

Management of human-machine dialogue involving multiple parties

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Seville, Spain

Guillermo Perez