Amazon Technologies, Inc.

Steven Todd Rabuchin

Gregory Michael Hart

Robert Vaughan Williams

James Robert Blair

Robert William Serr

Saiprasad Satya Kapila

Mark Chien

Farah Lynn Houston

Robert Pulciani

Antonio Melis

Manikya Pavan Kiran Pothukuchi

Michael Martin George

David Craig Yanacek

Gustavo Eduardo Lopez

Greg Roberts

Brandon Yarbrough

Robert Williams

Luis Valencia

Paul Damian Tidwell

John Benjamin Dalin

Daniel Zi Wang

Vicky Ge

Dylan Robert House

Amir Kabbara

Eric Sungmin Kim

Corey Calvin Badcock

Robert Anthony Pulciani, Jr

A system that is capable of controlling multiple entertainment systems and/or speakers using voice commands. The system receives voice commands and may determine audio sources and speakers indicated by the voice commands. The system may generate audio data from the audio sources and may send the audio data to the speakers using multiple interfaces. For example, the system may send the audio data directly to the speakers using a network address, may send the audio data to the speakers via a voice-enabled device or may send the audio data to the speakers via a speaker controller. The system may generate output zones including multiple speakers and may associate input devices with speakers within the output zones. For example, the system may receive a voice command from an input device in an output zone and may reduce output audio generated by speakers in the output zone.

Processing spoken commands to control distributed audio outputs

Techniques for providing a standardized voice user interface (VUI) that enables voice to voice natural language understanding (NLU) processing are described. The standardized VUI may be added to speechlets to enable a customer to interact with a business via server(s) using NLU processing. For example, a first user may initiate a first voice interaction using NLU processing with the server(s) and the system may initiate a second voice interaction using NLU processing between the server(s) and a second user. This enables a customer to initiate a transaction (e.g., request information, place an order, make a reservation, etc.) with the business using the speechlet. Thus, the business may use the speechlet to offer services without requiring additional infrastructure or complicated programming to implement.

Voice to voice natural language understanding processing

This disclosure describes a tabletop game assistant system configured to ingest and guide tangible games (such as board games, card games, etc.) using natural language interaction and image capture/visual display components. The system can include features enabling a game developer to 'teach' the system the rules of a game using natural language, such as written instructions, to reduce or eliminate the need for writing dedicated code. The system may process images of a game board and/or tokens such as game pieces and/or cards to further generate game data in the form of a logical game model. The system can use the game data to guide human players of the game and, in some cases, participate as a player itself. The system may further be configured to observe a game and detect invalid actions, answer questions regarding the rules, and suggest moves. The system may provide additional utilities such as generating a random output (e.g., rolling virtual dice) and learning to recognize new game pieces.

Natural language configuration and operation for tangible games

Exemplary embodiments relate to using a voice user interface for creating a poll to send to users. A poll requestor can create a poll using voice instructions and specify response options and setup information. After creating the poll, the system broadcasts it to users who can respond to the poll. The poll may be broadcasted while a user is receiving content. The users can respond using a voice user interface. The system compiles the responses and provides them to the poll requestor.

Polling with a natural language interface

Technologies are disclosed herein for optimizing in-application purchase (IAP) items to achieve a developer-specified success metric. Application developers can define customer segments and a success metric for each segment. In-application purchase items (IAP) for an application can be tuned for each customer segment in an attempt to achieve the defined success metric. The disclosed techniques can automatically determine the most compelling combination of attributes for an IAP item, such as item price, behavior, definition, and timing. Based on contextual information received from a number of resources, such as an application store, an e-commerce system, and a user device, an optimization service can modify attributes of the IAP items for users in the customer segment to achieve the developer-specified success metrics.

Optimizing in-application purchase items to achieve a developer-specified metric

A system that is capable of controlling multiple entertainment systems and/or speakers using voice commands. The system receives voice commands and may determine speakers playing output audio in proximity to the voice commands. The system may generate voice output and send the voice output to the speakers, along with a command to reduce a volume of output audio while playing the voice output. For example, the system may receive a voice command from an input device associated with an output zone, may reduce output audio generated by speakers in the output zone and may play the voice output via the speakers. In addition, the system may send the command to the speakers while sending the voice output to another device for playback. For example, the system may reduce output audio generated by the speakers and play the voice output via the input device.

Controlling distributed audio outputs to enable voice output

Disclosed are various embodiments for facilitating the purchase of excess items. In one embodiment, customer information and inventory data are retrieved from a merchant client. A determination is made on whether excess items exist. A list of target purchasers is generated based on data associated with a user account, and offers are generated and sent by electronic communication to the list of target purchasers.

Facilitating purchase of excess items

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Kirkland, WA, United States of America

Steven Todd Rabuchin