Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: One embodiment provides an apparatus. The apparatus includes crawler logic, indexer logic, natural language understanding (NLU) parser logic and a content data store. The crawler logic is to retrieve content. The indexer logic is to extract at least one of a sentence and/or a phrase and to identify a key term and a content element location identifier. The natural language understanding (NLU) parser logic is to classify the sentence and/or phrase based, at least in part, on semantic information and/or based, at least in part, on syntactic information. At least one of the indexer logic and/or the NLU parser logic is to store a content data record including a key term identifier, at least one of a semantic classification identifier and/or a syntactic classification identifier and the content element location identifier to the content data store.