Nant Holdingsip, LLC

Fluential, LLC

Nantmobile, LLC

Farzad Ehsani

Demitrios Leo Master

Silke Maren Witt-Ehsani

Eva M Knodt

Walter Rolandi

Elaine Drom Zuber

Jun Huang

Yookyung Kim

Youssef Billawala

A smart home interaction system is presented. It is built on a multi-modal, multithreaded conversational dialog engine. The system provides a natural language user interface for the control of household devices, appliances or household functionality. The smart home automation agent can receive input from users through sensing devices such as a smart phone, a tablet computer or a laptop computer. Users interact with the system from within the household or from remote locations. The smart home system can receive input from sensors or any other machines with which it is interfaced. The system employs interaction guide rules for processing reaction to both user and sensor input and driving the conversational interactions that result from such input. The system adaptively learns based on both user and sensor input and can learn the preferences and practices of its users.

Smart home automation systems and methods

A Mechanical Turk&#x2014;Integrated Development Environment system is disclosed. An integrated development environment (IDE) can include one or more interfaces capable of communicating with a mechanical turk engine. As a developer creates applications within the IDE, the developer can use the IDE to submit one or more requests to the mechanical turk engine. The engine constructs a mechanical turk project based on the requests and provides project tasks to workers. The results of the tasks can then be compiled and integrated back into the developer's application via the IDE. An example use includes constructing large domain specific data sets that can be applied to spoken dialog interfaces.

Mechanical turk integrated ide, systems and method

A device capable of splitting user input into phrases is presented. The disclosed device leverages multiple phrase splitting models to generate one or more possible split locations. The possible split locations can be derived based on leveraging multiple phrase splitting models. Each model contributes its suggested split locations to the set of possible split locations according to an implementation of a phrase splitting kernel algorithm that weights each model's suggestions.

Kernel-based verbal phrase splitting devices and methods

The invention enables creation of grammar networks that can regulate, control, and define the content and scope of human-machine interaction in natural language voice user interfaces (NLVUI). More specifically, the invention concerns a phrase-based modeling of generic structures of verbal interaction and use of these models for the purpose of automating part of the design of such grammar networks.

Phrase-based dialogue modeling with particular application to creating recognition grammars for voice-controlled user interfaces

A Mechanical Turk-Integrated Development Environment system is disclosed. An integrated development environment (IDE) can include one or more interfaces capable of communicating with a mechanical turk engine. As a developer creates applications within the IDE, the developer can use the IDE to submit one or more requests to the mechanical turk engine. The engine constructs a mechanical turk project based on the requests and provides project tasks to workers. The results of the tasks can then be compiled and integrated back into the developer's application via the IDE. An example use includes constructing large domain specific data sets that can be applied to spoken dialog interfaces.

Mechanical Turk integrated IDE, systems and methods

Mechanical Turk integrated IDE, systems and method

The performance of traditional speech recognition systems (as applied to information extraction or translation) decreases significantly with, larger domain size, scarce training data as well as under noisy environmental conditions. This invention mitigates these problems through the introduction of a novel predictive feature extraction method which combines linguistic and statistical information for representation of information embedded in a noisy source language. The predictive features are combined with text classifiers to map the noisy text to one of the semantically or functionally similar groups. The features used by the classifier can be syntactic, semantic, and statistical.

Robust information extraction from utterances

Interpretation from a first language to a second language via one or more communication devices is performed through a communication network (e.g. phone network or the internet) using a server for performing recognition and interpretation tasks, comprising the steps of: receiving an input speech utterance in a first language on a first mobile communication device; conditioning said input speech utterance; first transmitting said conditioned input speech utterance to a server; recognizing said first transmitted speech utterance to generate one or more recognition results; interpreting said recognition results to generate one or more interpretation results in an interlingua; mapping the interlingua to a second language in a first selected format; second transmitting said interpretation results in the first selected format to a second mobile communication device; and presenting said interpretation results in a second selected format on said second communication device.

Mobile speech-to-speech interpretation system

The invention enables creation of grammar networks that can regulate, control, and define the content and scope of human-machine interaction in natural language voice user interfaces (NLVUI). The invention enables phrase-based modeling of generic structures of verbal interaction to be used for the purpose of automating part of the design of such grammar networks. Most particularly, the invention enables such grammar networks to be used in providing a voice-controlled user interface to human readable text data that is also machine-readable (such as a Web page, a word processing document, a PDF document, or a spreadsheet).

Phrase-based dialogue modeling with particular application to creating a recognition grammar

A device interface system is presented. Contemplated device interfaces allow for construction of complex device behaviors by aggregating device functions. The behaviors are triggered based on conditions derived from environmental data about the device.

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Sunnyvale, CA, United States of America

Farzad Ehsani