A system and method incorporate prior knowledge into the optimization and regularization of a classification and regression model. The optimization may be a regularization process and the prior knowledge may be incorporated through adjustment of a cost function. A method of at least one processor developing a classification and regression model may be provided. The method may be implemented by at least one processor that implements classification and regression model functionality, including receiving training data and adjusting the model according to the training data; testing the classification and regression model; and employing prior knowledge during an optimization of the classification and regression model. The regularizing can include adjusting feature weights according to prior knowledge. In various embodiments, such systems and methods can be used in the processing of language inputs, e.g., speech and/or text inputs, to achieve greater interpretation accuracy.

A system and method incorporate prior knowledge into the optimization and regularization of a classification and regression model. The optimization may be a regularization process and the prior knowledge may be incorporated through adjustment of a cost function. A method of at least one processor developing a classification and regression model may be provided. The method may be implemented by at least one processor that implements classification and regression model functionality, including receiving training data and adjusting the model according to the training data; testing the classification and regression model; and employing prior knowledge during an optimization of the classification and regression model. The regularizing can include adjusting feature weights according to prior knowledge. In various embodiments, such systems and methods can be used in the processing of language inputs, e.g., speech and/or text inputs, to achieve greater interpretation accuracy.

An embodiment includes converting an original audio signal to an original text string, the original audio signal being from a recording of the original text string spoken by a specific person in a source language. The embodiment generates a translated text string by translating the original text string from the source language to a target language, including translation of a word from the source language to a target language. The embodiment assembles a standard phoneme sequence from a set of standard phonemes, where the standard phoneme sequence includes a standard pronunciation of the translated word. The embodiment also associates a custom phoneme with a standard phoneme of the standard phoneme sequence, where the custom phoneme includes the specific person's pronunciation of a sound in the translated word. The embodiment synthesizes the translated text string to a translated audio signal including the translated word pronounced using the custom phoneme.

An embodiment includes converting an original audio signal to an original text string, the original audio signal being from a recording of the original text string spoken by a specific person in a source language. The embodiment generates a translated text string by translating the original text string from the source language to a target language, including translation of a word from the source language to a target language. The embodiment assembles a standard phoneme sequence from a set of standard phonemes, where the standard phoneme sequence includes a standard pronunciation of the translated word. The embodiment also associates a custom phoneme with a standard phoneme of the standard phoneme sequence, where the custom phoneme includes the specific person's pronunciation of a sound in the translated word. The embodiment synthesizes the translated text string to a translated audio signal including the translated word pronounced using the custom phoneme.

Methods, systems, and computer-readable media for generating videos with characters indicating regions of images are provided. For example, an image containing a first region may be received. At least one characteristic of a character may be obtained. A script containing a first segment of the script may be received. The first segment of the script may be related to the first region of the image. The at least one characteristic of a character and the script may be used to generate a video of the character presenting the script and at least part of the image, where the character visually indicates the first region of the image while presenting the first segment of the script.

Methods, systems, and computer-readable media for generating videos with characters indicating regions of images are provided. For example, an image containing a first region may be received. At least one characteristic of a character may be obtained. A script containing a first segment of the script may be received. The first segment of the script may be related to the first region of the image. The at least one characteristic of a character and the script may be used to generate a video of the character presenting the script and at least part of the image, where the character visually indicates the first region of the image while presenting the first segment of the script.

In one example of the disclosure, a machine-translation for each of a plurality of strings is determined, the strings for display upon execution of a subject application. A first display of a test step to be performed by a test application during execution of the subject application is caused. A second display of a state for the subject application that includes the plurality of strings is caused concurrent with the first display. A user-translation for each of the strings is obtained, the user-translations provided via a GUI included within the second display. A translation property file associated with the subject application is amended to include the user-translations.

Technology is disclosed for snippet pre-translation and dynamic selection of translation systems. Pre-translation uses snippet attributes such as characteristics of a snippet author, snippet topics, snippet context, expected snippet viewers, etc., to predict how many translation requests for the snippet are likely to be received. An appropriate translator can be dynamically selected to produce a translation of a snippet either as a result of the snippet being selected for pre-translation or from another trigger, such as a user requesting a translation of the snippet. Different translators can generate high quality translations after a period of time or other translators can generate lower quality translations earlier. Dynamic selection of translators involves dynamically selecting machine or human translation, e.g., based on a quality of translation that is desired. Translations can be improved over time by employing better machine or human translators, such as when a snippet is identified as being more popular.

A corpus generation device and method, the device comprising: a segmentation module, connected to at least one monolingual parallel corpus for segmenting a sentence into words and processing the segmented words by a knowledge-driven approach; a classification module, for classifying sentences having different tag sequences but the same meaning into the same sentence cluster; a mapping module, for determining the categories of sentence structures of all the sentences in the sentence cluster, recording and storing a mapping mode for transforming tags between sentence structures when different categories of sentence structures in the same sentence cluster are transformed; a sentence structure generation module, for generating sentence structures according to a first mapping mode between a first category of sentence structures in one of the sentence clusters and other categories of sentence structures in the same sentence cluster; and a corpus generation module, for nesting a word corresponding to a sequence tag to generate a new monolingual parallel corpus.

A user is enabled to interact with a virtual world environment using an instant messenger application by enabling a user to enter the virtual world environment using the instant messenger application that includes an instant messaging (IM) user interface, generating and managing an avatar to represent the user in the virtual world environment, monitoring a sub-portion of the virtual world environment corresponding to a current location of the user in the virtual world environment, determining descriptions of activities taking place in the sub-portion of the virtual world environment based on the monitoring, and providing the user with the determined descriptions of activities taking place in the sub-portion of the virtual world environment via the IM user interface.