Microsoft Technology Licensing, LLC

David Ernesto Heekin Burkett

Jesse Daniel Eskes Rusak

Jayant Sivarama Krishnamurthy

Jonathan Reed Harris

Ashok Kuppusamy

David Leo Wright Hall

Jaclyn Carley Knapp

Daniel Louis Klein

Richard Leigh Mains

Michael Francis Palermiti, Ii

Chad Steven Estes

Allison Anne O'Mahony

Harris Syed

Diego Hernan Carlomagno

Talon Edward Ireland

Jose Miguel Rady Allende

Andrew Paul McGovern

Daniel Lawrence Roth

Viktoriya Taranov

Jordan Rian Cohen

Adam David Pauls

Jacob Daniel Andreas

Jason Andrew Wolfe

Tudor Buzasu Klein

Sergiy Gavrylenko

Alexander J Kolmykov-Zotov

John P Bufe, Iii

Alan Xinyu Guo

Andrew Paul Mcgovern

Various embodiments discussed herein enable client applications to be heavily integrated with a voice assistant in order to perform commands associated with voice utterances of users via voice assistant functionality and also seamlessly cause client applications to automatically perform native functions as part of executing the voice utterance. Such heavy integration also allows particular embodiments to support multi-modal input from a user for a single conversational interaction. In this way, client application user interface interactions, such as clicks, touch gestures, or text inputs are executed alternative or in addition to the voice utterances.

Voice assistant-enabled client application with user view context and multi-modal input support

Various embodiments discussed herein enable client applications to be heavily integrated with a voice assistant in order to both perform commands associated with voice utterances of users via voice assistant functionality and also seamlessly cause client applications to automatically perform native functions as part of executing the voice utterance. For example, some embodiments can automatically and intelligently cause a switch to a page the user needs and automatically and intelligently cause a population of particular fields of the page the user needs based on a user view context and the voice utterance.

Voice assistant-enabled client application with user view context

A system that provides a sharable language interface for implementing automated assistants in new domains and applications. A dialogue assistant that is trained in a first domain can receive a specification in a second domain. The specification can include language structure data such as schemas, recognizers, resolvers, constraints and invariants, actions, language hints, generation template, and other data. The specification data is applied to the automated assistant to enable the automated assistant to provide interactive dialogue with a user in a second domain associated with the received specification. In some instances, portions of the specification may be automatically mapped to portions of the first domain. By having the ability to learn new domains and applications through receipt of objects and properties rather than retooling the interface entirely, the present system is much more efficient at learning how to provide interactive dialogue in new domains than previous systems.

Developer platform for providing automated assistant in new domains

A method comprising recognizing a user utterance including an ambiguity. The method further comprises using a previously-trained code-generation machine to produce, from the user utterance, a data-flow program including a search-history function. The search-history function is configured to select a highest-confidence disambiguating concept from one or more candidate concepts stored in a context-specific dialogue history.

Ambiguity resolution with dialogue search history

A method, comprising recognizing a user utterance for processing. The method further comprises using a previously-trained code-generation machine to generate, from the user utterance, a data-flow program configured to produce a return value upon successful execution. The method further comprises beginning execution of the data-flow program. Responsive to reaching an error condition resulting from execution of the data-flow program, the method further comprises, prior to the data-flow program producing the return value, suspending execution of the data flow program. The method further comprises using the previously-trained code-generation machine to generate an error-handling data-flow program, wherein the error-handling data-flow program is configured to produce the return value; beginning execution of the error-handling data-flow program to produce the return value; and outputting the return value.

Error recovery for conversational systems

Growing community of inventors

Berkeley, CA, United States of America

David Ernesto Heekin Burkett