Amazon Technologies, Inc.

Vikas Jain

Sumedha Arvind Kshirsagar

Shishir Sridhar Bharathi

Ajay Gopalakrishnan

David Robert Thomas

Nishant Kumar

Jeff Bradley Beal

Vikram Kumar Gundeti

Vaibhav Jain

Sharatkumar Nagesh Kuppahally

Giuseppe Di Fabbrizio

Rohan Mutagi

Fred Torok

John Daniel Thimsen

Frédéric Johan Georges Deramat

Peter Paul Henri Carbon

Shamitha Somashekar

Michael Dale Whiteley

Andrew Christopher Miles

Tudor Toma

Ling Hu

Cory Curtis Manthei

Various systems and methods of tracking database partition change log dependencies are described herein. A system is disclosed herein, according to some embodiments. A change log for a database partition of the plurality of database partitions is stored to a log store. An indication that a split of the database partition into two or more child database partitions has occurred is received. Responsive to the split of the database partition, the change log is split into two or more corresponding child change logs. A portion of the change log is deleted responsive to a determination that a respective complete snapshot is stored for each child database partition corresponding to a child change log of the change log and a determination that a retention window for the portion of the change log has passed.

Tracking database partition change log dependencies

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

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

Dialog management context sharing

An open framework for computing devices to dispatch voice-based interactions to supporting applications. Applications are selected on a trial-and-error basis to find an application able to handle the voice interaction. Dispatching to the applications may be performed without a determination of meaning conveyed in the interaction, with meaning determined by the individual applications. Once an application acts upon a voice interaction, that application may be given first-right-of-refusal for subsequent voice interactions.

Voice interaction application selection

A voice-based system may comprise a local speech interface device and a remote control service. A user may interact with the system using speech to obtain services and perform functions. The system may allow a user to install applications to provide enhanced or customized functionality. Such applications may be installed on either the speech interface device or the control service. The control service receives user speech and determines user intent based on the speech. If an application installed on the control service can respond to the intent, that application is called. Otherwise, the intent is provided to the speech interface device which responds by invoking one of its applications to respond to the intent.

Voice application architecture

Network-based services may be provided to a user through the user of a speech-based user device located within a user environment. The speech-based user device may accept speech commands from a user and may also interact with the user by means of generated speech. Operating state of the speech-based user device may be provided to the network-based service and stored by the service. Applications that provide services through the speech-based interface may request and obtain the stored state information.

Storing state information from network-based user devices

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Bellevue, WA, United States of America

Vikas Jain