Microsoft Technology Licensing, LLC

Speechace LLC

Chun Ho Cheung

Abhishek Gupta

Ran Kalach

James Robert Benton

Kashif Hasan

Paul Adrian Oltean

Ahmed El-Shimi

Jin Li

Sudipta Sengupta

Ping Xie

Mathew James Dickson

Ronakkumar N Desai

Chenguang Zhu

Seung-Yup Chai

Daniel Hefenbrock

Joerg-Thomas Pfenning

Peter Wassmann

Nicholas R Leggett

Stephen T Owen

One or more implementations allow for systems, methods, and devices for teaching and/or assessment of one or more spoken language skills through analysis of one or more pronunciation characteristics of one or more individual language components of a teaching string audio sample data that corresponds to the user's speaking of the teaching string.

Teaching and assessment of spoken language skills through fine-grained evaluation

The subject disclosure is directed towards partially recalling file ranges of deduplicated files based on tracking dirty (write modified) ranges (user writes) in a way that eliminates or minimizes reading and writing already-optimized adjacent data. The granularity of the ranges does not depend on any file-system granularity for tracking ranges. In one aspect, lazy flushing of tracking data that preserves data-integrity and crash-consistency is provided. In one aspect, also described is supporting granular partial recall on an open file while a data deduplication system is optimizing that file.

Granular partial recall of deduplicated files

The subject disclosure is directed towards using primary data deduplication concepts for more efficient access of data via content addressable caches. Chunks of data, such as deduplicated data chunks, are maintained in a fast access client-side cache, such as containing chunks based upon access patterns. The chunked content is content addressable via a hash or other unique identifier of that content in the system. When a chunk is needed, the client-side cache (or caches) is checked for the chunk before going to a file server for the chunk. The file server may likewise maintain content addressable (chunk) caches. Also described are cache maintenance, management and organization, including pre-populating caches with chunks, as well as using RAM and/or solid-state storage device caches.

Caching content addressable data chunks for storage virtualization

The subject disclosure is directed towards a data storage service that uses hash values, such as substantially collision-free hash values, to maintain data integrity. These hash values are persisted in the form of mappings corresponding to data blocks in one or more data stores. If a data error is detected, these mappings allow the data storage service to search the one or more data stores for data blocks having matching hash values. If a data block is found that corresponds to a hash value for a corrupted or lost data block, the data storage service uses that data block to repair the corrupted or lost data block.

Data error detection and correction using hash values

The subject disclosure is directed towards transforming a file having at least one undeduplicated portion into a fully deduplicated file. For each of the at least one undeduplicated portion, a deduplication mechanism defines at least one chunk between file offsets associated with the at least one undeduplicated portion. Chunk boundaries associated with the at least one chunk are stored within deduplication metadata. The deduplication mechanism aligns the at least one chunk with chunk boundaries of at least one deduplicated portion of the file. Then, the at least one chunk is committed to a chunk store.

Optimization of a partially deduplicated file

The subject disclosure is directed towards changing a file from a fully deduplicated state to a partially deduplicated state in which some of the file data is deduplicated in a chunk store, and some is recalled into the file, that is, in the file's storage volume. A partial recall mechanism such as in a file system filter tracks (e.g., via a bitmap in a file reparse point) whether file data is maintained in the chunk store or has been recalled to the file. Data is recalled from the chunk store as needed, and committed (e.g., flushed) to the file. Also described is efficiently returning the file to a fully deduplicated state by using the tracking information to determine which parts of the file are already deduplicated into the chunk store so as to avoid their further deduplication processing.

Partial recall of deduplicated files

Navigational functionality is abstracted from user interface pages associated with a wizard and allocated to a navigation module. The navigation module provides a hierarchical tree of nodes representative of the user interface pages in the wizard. In operation, a token is transmitted from a user interface page to the navigation module when a user activates a user interface control within the user interface pages. The token instructs the navigation module to traverse the hierarchical tree to determine a successor page to present to the user, such as a next user interface page, a previous user interface page, a user interface page defining a selected branch, and so on. Abstracting navigational information from individual user interface pages is advantageous because it simplifies the design and modification of user interface pages, as well as promotes the modularity and portability of the user interface pages.

Hierarchical navigation layers for wizards

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Redmond, WA, United States of America

Chun Ho Cheung