Amazon Technologies, Inc.

Sumedha Arvind Kshirsagar

Christo Frank Devaraj

Jeff Bradley Beal

Gregory Michael Hart

Ajay Gopalakrishnan

Nishant Kumar

Brian Alexander Oliver

Venkatesh Kancharla

Christopher Geiger Parker

Ran Mokady

Kevin Robert Charter

Vikas Jain

Shishir Sridhar Bharathi

David Robert Thomas

James Alexander Stanton

Aaron Takayanagi Barnet

Aparna Nandyal

Arun Rajendran

Someshwaran Elangovan

John Daniel Thimsen

Giuseppe Di Fabbrizio

Shamitha Somashekar

Thomas Schaaf

Robert David Owen

Rafal Kuklinski

Remus Razvan Mois

Derek Christopher Murman

Tudor Toma

Ling Hu

Roger Alix-Gaudreau

A speech recognition platform configured to receive an audio signal that includes speech from a user and perform automatic speech recognition (ASR) on the audio signal to identify ASR results. The platform may identify: (i) a domain of a voice command within the speech based on the ASR results and based on context information associated with the speech or the user, and (ii) an intent of the voice command. In response to identifying the intent, the platform may perform multiple actions corresponding to this intent. The platform may select a target action to perform, and may engage in a back-and-forth dialog to obtain information for completing the target action. The action may include streaming audio to the device, setting a reminder for the user, purchasing an item on behalf of the user, making a reservation for the user or launching an application for the user.

Outcome-oriented dialogs on a speech recognition platform

Systems and methods for sender profile and/or recipient profile disambiguation and/or confirmation are disclosed. In instances where a sender profile is not indicated by a user sending a communication from a communal device, heuristic data may be utilized to infer the sender profile. Similar heuristic data may also be used when selection of the sender profile is associated with a low confidence level. Heuristic data may also be used to infer the recipient profile when the user does not indicate the recipient profile or when selection of the recipient profile is associated with a low confidence. Various confirmations may result from the sender and recipient profile disambiguation.

Sender and recipient disambiguation

Features are disclosed for performing functions in response to user requests. Natural Language Understanding ('NLU') processing may be performed to generate command data that represents a subject of an utterance. The command data may be sent to an application that causes presentation of first output content in a first modality at a first time in response to receiving the command data, and generates second output content in a second modality different from the first modality, wherein the second output content is associated with the first output content. The second output content may be presented in the second modality at a second time subsequent to the first time.

Dialog management with multiple modalities

Methods and systems for providing message playback using a shared electronic device is described herein. In response to receiving a request to output messages, a speech-processing system may determine a group account associated with a requesting device, and may determine messages stored by a message data store for the group account. Speaker identification processing may also be performed to determine a speaker of the request. A user account associated with the speaker, and messages stored for the user account, may be determined. A summary response indicating the user account's messages and the group account's message may then be generated such that the user account messages are identified prior to the group account's messages. The messages may then be analyzed to determine an appropriate voice user interface for the requester such that the playback of the messages using a shared electronic device is more natural and conversational.

Message playback using a shared device

Systems and methods to combine related messages are disclosed. Multiple messages may be combined into a single message for display and output on one or more devices based on one or more factors. The factors may include, for example, a determination that the multiple messages were sent by and/or received from the same device, user, user profile, and/or user account. The facts may also include a determination that the multiple messages were sent within a threshold amount of time of each other and/or that the messages have the same or similar themes.

Message grouping

Methods and systems for performing contact resolution are described herein. When initiating a communications session using a voice activated electronic device, a contact name may be resolved to determine an appropriate contact with which the communications session may be directed to. Contacts from an individual's contact list may be queried to determine a listing of probable contacts associated with the contact name, and contact identifiers associated with the contact may be determined. Using one or more rules for disambiguating between similar contact names, a single contact may be identified, and a communications session with that contact may be initiated.

Contact resolution for communications systems

Dialog visualizations are created to enable analysis of interactions between a user and a speech recognition system used to implement user commands. Spoken commands from the user may be classified, along with system responses to the spoken commands, to enable aggregation of communication exchanges that form dialog. This data may then be used to create a dialog visualization. The dialog visualization may enable an analyst to visually explore different branches of the interactions represented in the dialog visualization. The dialog visualization may show a trajectory of the dialog, which may be explored in an interactive manner by the analyst.

Dialog visualization

Features are disclosed for performing functions in response to user requests based on contextual data regarding prior user requests. Users may engage in conversations with a computing device in order to initiate some function or obtain some information. A dialog manager may manage the conversations and store contextual data regarding one or more of the conversations. Processing and responding to subsequent conversations may benefit from the previously stored contextual data by, e.g., reducing the amount of information that a user must provide if the user has already provided the information in the context of a prior conversation. Additional information associated with performing functions responsive to user requests may be shared among applications, further improving efficiency and enhancing the user experience.

Dialog management with multiple applications

Growing community of inventors

Seattle, WA, United States of America

Sumedha Arvind Kshirsagar