Network-accessible services that provide post-production digital compositing and motion graphics authoring to users who provide their own core content, which the services supplement via a user-driven interface through the inclusion of digital still images, artwork, video, sound, and/or other supplemental content selected by the user. In one embodiment, following selection and sequencing of the various core and supplemental content components, the services automatically generate and make available to a user a finished product that integrates core and supplemental content. To simplify the compositing task, a series of pre-formatted motion graphics video templates may be made available. The end product provided by aspects of the present invention may be a professional-quality ensemble motion graphics video production that may be delivered in any popular format, such as AVI, JPEG, MPEG4 and the like to the customer and or to selected recipients via download or common carrier.

Computer-implemented methods and computer-readable storage media are disclosed for facilitating browser-based, what-you-see-is-what-you-get (WYSIWYG) editing of an extensible markup language (XML) file. A browser executing on a local computing system is used to access a hypertext markup language (HTML) representation of an extensible markup language (XML) file. The HTML representation includes a plurality of elements of the XML file formatted in accordance with an extensible stylesheet language (XSL) transform associated with the XML file. A plurality of editing handlers is inserted within the HTML representation to facilitate modifying the HTML representation and applying the changes to the XML file. A user is permitted to modify the HTML representation for purposes of applying the modifications to the XML file.

Methods for optimizing a scale and position of a document in response to a user input is provided are provided. In one aspect, a method includes receiving an initial input request to scroll a document to a target position of the document, and identifying at least one relevant portion of content at or near the target position of the document. The method also includes adjusting a position and scale of the document while receiving the initial input request to an optimal position and an optimal scale for viewing the at least one relevant portion. Systems and machine-readable media are also provided.

Embodiments of the present invention provide an approach for estimating the accuracy of a transcription of a voice recording. Specifically, in a typical embodiment, each word of a transcription of a voice recording is checked against a customer-specific dictionary and/or a common language dictionary. The number of words not found in either dictionary is determined. An accuracy number for the transcription is calculated from the number of said words not found and the total number of words in the transcription.

A computer implemented method and system for managing browser tabs includes identifying a plurality of URLs (Uniform Resource Locator(s)) in response to detecting the URLs in a web browser running on a computer. The plurality of URLs are organized based on each of the URLs, and each of the plurality of URLs correspond to a tab opened by the web browser. The tabs of the web browser are grouped based on the URLs.

A computer-implemented method for representing sequences of bits, the method comprising the steps of: obtaining access to at least one dictionary, wherein each dictionary comprises entries of one type of part of speech each indexed with a unique key value (501); reading an input sequence of an input sequence of bits, the sequence being of a defined length (502); and splitting the input sequence into at least one subsequence, the at least one subsequence covering the complete input sequence, wherein each subsequence is associated with a part-of-speech dictionary and is represented by the associated dictionary's entry having a key value of the subsequence (503).

Machine logic that automatically detects natural language processing (NLP) system annotation errors and correspondingly updates NLP annotators to prevent future erroneous annotations by performing the following steps: (i) determining that a first annotation error has occurred in an annotation of a corpus by the natural language processing system; (ii) generating a candidate set of annotation correction actions, where each annotation correction action of the set is adapted to prevent an occurrence of an error similar to the first annotation error by the natural language processing system; (iii) selecting an annotation correction action from the candidate set of annotation correction actions, based, at least in part, on a set of annotation correction confidence characteristics; and (iv) automatically applying the selected annotation correction action to the natural language processing system.