Microsoft Technology Licensing, LLC

Kati Amanda London

Joseph Edwin Johnson, Jr

Dustin Isaac Abramson

Ying Wang

Emmanouil Koukoumidis

Di Li

Hailong Mu

Donald Brinkman

Zhan Chen

Hudong Wang

Steven G Zittrower

Kelli A Stuckart

Brandon Scott Jones

Kevin Michael Munoz

Maria A Rangel

Pengfei Hao

Don Edward Diekneite

Wei-Ying Ma

Ming Zhou

Lei Cui

Lars Hasso Liden

Furu Wei

Shaohan Huang

Oussama Elachqar

Haoyong Zhang

Derrick Fu

James Bigbee Garver

Zhiying Zhang

Yu-Ting Kuo

Aspects of the present disclosure provide systems and methods for detecting memorable events of a user, storing those memorable events in a user profile, and leveraging those events to the user. In so doing, memorable events with positive emotional weight may be recalled to encourage delightful experiences. Alternatively or additionally, memorable events with negative emotional weight may be recalled to increase user engagement for conversational systems.

Memorable event detection, recording, and exploitation

Among other things, embodiments of the present disclosure may be used to help train speech recognizers for improving generalized voice experience quality in a chat bot system. In some embodiments, the system provides users with games to play to increase user engagement with the chat bot system.

Voice synthesized participatory rhyming chat bot

Systems and methods may be used to process and output information related to a non-speech vocalization, for example from a user attempting to mimic a non-speech sound. A method may include determine a mimic quality value associated with an audio file by comparing a non-speech vocalization to a prerecorded audio file. For example, the method may include determining an edit distance between the non-speech vocalization and the prerecorded audio file. The method may include assigning a mimic quality value to the audio file based on the edit distance. The method may include outputting the mimic quality value.

Audio processing for voice simulated noise effects

An example environment can automatically generate content for a conversation in response to a presented content item. An example computing device receives information associated with a content item produced by a source system, the content item being accessible to other the computing devices via a network. In response to receiving the information, the computing device identifies a start comment. In response to identifying the start comment, the computing device identifies a reply to the start comment using at least a ranking model.

Automatic conversation creator for news

Described herein are various technologies pertaining to assigning an emotional state to a computer-implemented entity. The emotional state is a function of data values in a data stream output by a data source, such as a sensor or a web service. The data values in the data stream are processed over time to generate a measure value. Values that are indicative of a dynamic state of a measure relative to an optimal measure state are computed and assigned to the measure based upon the measure value. A reaction of the computer-implemented entity is determined based upon these values. A customized personality for the computer-implemented entity maps reactions to respective emotional states, and an emotional state that is mapped to the reaction is assigned to the computer-implemented entity.

Assignation of emotional states to computer-implemented entities

Systems and methods for personality consistent automated chatting are provided. The systems and methods track the emotional state of the chat bot, track entity related dispositions of the chat bot and/or track the closeness of the relationship between the chat bot and a user. Accordingly, the systems and methods are able to provide consistent personality and/or points of view by generating replies based on the tracked chat bot emotional state, chat bot entity dispositions, and/or the relationship closeness between the chat bot and the user.

Systems and methods for a personality consistent chat bot

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New York, NY, United States of America

Kati Amanda London