Amazon Technologies, Inc.

Microsoft Technology Licensing, LLC

Munir Mahmood

Vikram Kumar Gundeti

Rongzhou Shen

Bo Li

Leopold Bushkin

Yaser Khan

Shemyla Anwar

Alexander Thomas Loeb

Mohammed Arif

Edward Page Foyle

Michael F Schwartz

Karvell Li

David John Law

Rahul Sudhir Kumar

Mohammed Nazeeruddin

Danpo Zhang

Gilbert Martin McQuillan

Jamie Marconi

Gupta Garuda

Robert M Hyman

Barry I Kelman

Sachin Kukreja

Miriam Borkenhagen

Risto Fermin Rangel Kuoppa

Sergio Damo De Lemos

Elaine Lan Chen

Techniques for a natural language processing (NLP) system to implement more than one assistant are described. The NLP system may receive a natural language input corresponding to more than one user command. The NLP system may respond to a first command, of the natural language input, using a TTS voice of a first NLP system assistant. The NLP system may respond to a second command, of the natural language input, using a TTS voice of a second NLP system assistant.

Multi-assistant natural language input processing

Techniques for a natural language processing (NLP) system to implement more than one assistant are described. The NLP system may receive a natural language input from a device. The NLP system may also receive one or more signals representing one or more assistants to be implemented with respect to the natural language input. The NLP system may intelligently select an assistant to be invoked with respect to the natural language input. Once the assistant is selected, the NLP system may cause content, output to a user, to have characteristics specific to the assistant.

Multi-assistant natural language input processing to determine a voice model for synthesized speech

A system for processing a seller provided input image depicting an object. The system may process the input images to be in compliance with an online shopping website's image requirements. The image processing service may execute multiple modules on the input image. An edge detection module may detect one or more edges of the image of the object and determine border data indicative of a border around the object. An object of interest module may extract the image of the object within the border to generate an object of interest image. A background extraction module may create one or more closed shapes to separate the image of the object from background pixels. A hole detection module may traverse the one or more closed shapes to determine a presence of background pixels, remove the background pixels, and generate a resulting image.

System and apparatus for image processing

User profile data that may be spread across different service providers and that may vary across different service providers can be aggregated to provide an aggregate user profile. An aggregate user profile can be generated regardless of, among other things, varying user profile semantics, differing data formats, data item conflicts, evolving server protocols and interfaces, and updates to the number, identity, location, and type of servers upon which the service providers are maintained.

User profile aggregation

Methods and systems for resolving naming contests when a user seeks to register an account associated with a login identifier that is already in use by another user. An authentication server notifies the user of a contested registration when the requested login identifier, such as an e-mail address, matches one of the identifiers stored in an authentication database. The server then solicits confirmation from the user that the login identifier belongs to the requesting user rather than the earlier user. By forcing the earlier user to select a different login identifier, the server renders the existing user account inactive but retains a unique account identifier and associated account information for the inactive user account.

Contested account registration

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Bellevue, WA, United States of America

Munir Mahmood