Microsoft Technology Licensing, LLC

Olivier Nano

Tihomir Tsvetkov Tarnavski

Ivo José Garcia Dos Santos

Ivo Jose Garcia Dos Santos

Eldar Akchurin

Ramkumar Krishnan

Sebastien Peray

Marcel Tilly

Xuedong D Huang

Lev Novik

Arul A Menezes

Tanvi Surti

William Duncan Lewis

Laurent Bussard

Christian Wendt

Royi Ronen

Oron Nir

Avner Levi

Ohad Jassin

Ika Bar-Menachem

Panos Periorellis

Mor Geva Pipek

Ori Ziv

Stephan Grell

Jonathan David Goldstein

Badrish Chandramouli

Clemens Alden Szyperski

Mark Gilbert

Ziv Kasperski

Panagiotis Periorellis

Dirk Siemer

Alex Raizman

Dipanjan Banik

Systems and methods may be used to provide transcription and translation services. A method may include initializing a plurality of user devices with respective language output selections in a translation group by receiving a shared identifier from the plurality of user devices and transcribing the audio stream to transcribed text. The method may include translating the transcribed text to one or more of the respective language output selections when an original language of the transcribed text differs from the one or more of the respective language output selections. The method may include sending, a user device in the translation group, the transcribed text including translated text in a language corresponding to the respective language output selection for the user device. In an example, the method may include customizing the transcription or the translation, such as to a particular topic, location, user, or the like.

Customized transcribed conversations

In various embodiments, methods and systems for implementing a media management system, for video data processing and adaptation data generation, are provided. At a high level, a video data processing engine relies on different types of video data properties and additional auxiliary data resources to perform video optical character recognition operations for recognizing characters in video data. In operation, video data is accessed to identify recognized characters. A video OCR operation to perform on the video data for character recognition is determined from video character processing and video auxiliary data processing. Video auxiliary data processing includes processing an auxiliary reference object; the auxiliary reference object is an indirect reference object that is a derived input element used as a factor in determining the recognized characters. The video data is processed based on the video OCR operation and based on processing the video data, at least one recognized character is communicated.

Media management system for video data processing and adaptation data generation

Customized multi-device translated conversations

A method is described of pre-processing real-time data to be processed by one or more real-time analytics services. The method includes: receiving, at a stateless ingress node, data from one or more client devices; transforming the data in real-time at the stateless ingress node; determining in real-time, at the stateless ingress node, a real-time analytics service for the transformed data; and forwarding in real-time the transformed data to the determined real-time analytics service for stateful processing.

Scalable data enrichment for cloud streaming analytics

Methods, systems, and computer-readable media for analyzing a query are disclosed. A particular method includes receiving data representing an event flow associated with execution of a query that includes a plurality of operators. A graph is generated that includes a plurality of nodes that corresponds to operators of the query, and edges of the graph that correspond to streams between operators of the query. The method includes receiving an input identifying a particular node of the graph, where the particular node corresponds to a particular operator of the query. In response to the input, an output associated with at least one event processed by the particular operator is displayed.

Visual analysis and debugging of event flows

Customized multi-device translated and transcribed conversations

The formulation of transformations on one or more input event streams to generation one or more output event streams. Accordingly, the transformations may be considered to be a query on the original input event stream(s). The event query includes event stream source representations representing an input event stream available in a particular execution context. The event query also includes a transformation module identifying the transformation set to be performed on the input event streams in the execution context. Once the query is properly formed, an execution module may then cause the transformations to be executed upon the designated input event stream(s) to generate output event streams.

Event stream transformations

Methods of managing distributed analytics on device groups are described. In an embodiment, a management service within a distributed analytics system provides an interface to allow a user to define a group of devices based on a property of the devices. When the property of a device in the system satisfies the criterion specified by the user, the device is added to the group and the device may subsequently be removed from the group if the device no longer satisfies the criterion. Once a group has been defined, the management service enables users to specify management operations, such as creating, starting, stopping or deleting queries or management operations relating to other entities of end devices, which are to be implemented on all the devices in the group and the management service propagates the operation to all devices in the group, irrespective of their current connectivity status.

Managing distributed analytics on device groups

An analysis module is configured to receive data associated with an event flow. The data is received from a first analysis module (e.g., in a stack of analysis modules) or from the event flow. The analysis module is configured to execute an analysis operation on the data to generate a result. The analysis module can output the result to a second analysis module (e.g., in the stack of analysis modules) or to a user interface.

Analysis stack for an event flow

Embodiments described herein are directed to methods, and systems for generating event processing language code in a development environment using an event processing compiler. A query in event processing language is received in a development environment. The query can be associated with sample data from input files or an input data source. An event processing compiler compiles the query, where the compiler transforms the query from event processing language code to a development environment script language code. In particular, the event processing language code transforms the code based on event processing attributes that are intricately aligned in syntax and semantic between the event processing language and the development environment script language. The query as a development environment script is executed using sample data. Executing the query generates output comprising final results data, intermediate results data, and provides for display warnings when mismatches exist between the results data and output specifications.

Event processing development environment

Embodiments described herein are directed to methods and systems for enhanced event processing. An enhanced event processing request is received, the enhanced processing request comprising an indication of input data from a database data source. The input data indicated in the enhanced event processing request is accessed using a constructed data stream. The constructed data stream provides access to a collection of snapshots over time of database data of the database data source. The data from constructed data stream source may be accessed as a function of a selected value and a selected time. The constructed data stream data includes the temporal element, which is unavailable with the database data, the temporal element facilitates performing enhanced event processing for the database data using the constructed data stream data. An output for the enhanced event processing request is generated based on the input data accessed using the constructed data stream data.

Constructed data stream for enhanced event processing

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Aachen, Germany

Olivier Nano