A computer implemented language interpretation/translation platform is provided. The computer implemented language interpretation/translation platform comprises a processor that establishes a video remote interpretation session between a mobile device associated with a user and a computing device associated with a language interpreter/translator, receives data corresponding to a context of the video remote interpretation session from the mobile device, and augments the video remote interpretation session with one or more features that are distinct from a language interpretation service.

Methods and systems of using machine learning to create a trusted model that improves the operation of a computer system controller are provided herein. In some embodiments, a machine learning method includes training a model using input data, extracting the model, and determining whether the model satisfies the trust-related constraints. If the model does not satisfy the trust-related constraint, modifying at least one of: the model using one or more model repair algorithms, the input data using one or more data repair algorithms, or a reward function of the model using one or more reward repair algorithms, and re-training the model using at least one of the modified model, the modified input data, or the modified reward function. If the model satisfies the trust-related constraints, providing the model as a trusted model that enables a computer system controller to perform system actions within predetermined guarantees.

The present disclosure relates to computer-implemented methods and computer systems for providing user-friendly and understandable presentations of Open Data (OData) Protocol resources through an automatic translation and modification process. The present disclosure provides a user interface tool for presenting and browsing OData fees that can provide a visualization of an OData feed structure to users in an otherwise unavailable format. In particular, developers can view and modify resources outside of the underlying format in which such OData feeds are traditionally presented. The user interface tool can provide an out-of-box user interface with which a developer can view and modify resources associated with a feed, browse related entity sets, set filters, and perform other operations. In essence, the user interface tool can decrease user's efforts and difficult in understanding particular OData feeds and the entities associated therewith.

Systems and techniques for facilitating digital data prognostics are presented. A system can processes a corpus of stored data, generate respective digital signatures representing respective subsets of the corpus of the stored data, and tag the respective digital signatures with tags corresponding to extrinsic events. The digital signatures can be stored and indexed in a digital signature library. The system can also compare a new digital signature to learned digital signatures in order to identify one or more matches, and prognose an upcoming event associated with the new digital signature based on the matches and generated inferences for the learned digital signatures.

Creation data can be received from a computer-readable developer profile, with the creation data including instructions to create a messaging bot. A messaging bot definition can be generated using the instructions, and a messaging bot may be executed using the definition. The instructions may include natural language instructions defining one or more messaging bot characteristics. The natural language instructions can be matched with one or more commands to include one or more characteristics in the messaging bot, and instructions for those characteristic(s) can be included in the messaging bot definition. The instructions can be instructions that are not in a computer programming language, and they can be instructions to create one or more general messaging bot characteristics configured to be implemented with a specific dialog structure that defines one or more specific natural language dialog scripts.

A computer system can conduct corresponding natural language dialogs with multiple computer-readable profiles using a computer proxy messaging bot. For example, a first set of natural language instructions can be received via a computer messaging proxy bot from a first computer-readable profile. The first set of natural language instructions can be analyzed via the proxy bot. Also, first and second natural language dialog scripts can be generated via the proxy bot using results of the analyzing of the first set of natural language instructions, with the second natural language dialog script including natural language data derived from the first set of natural language instructions. The first natural language dialog script can be sent to the first profile via the proxy bot and the second natural language dialog script can be sent to a second computer-readable profile via the proxy bot, both in response to the first set of instructions.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, relating to synthetic call status updates. In some implementations, a method includes determining, by a task manager module, that a triggering event has occurred to provide a current status of a user call request. The method may then determine, by the task manager module, the current status of the user call request. A representation of the current status of the user call request is generated. Then, the generated representation of the current status of the user call request is provided to the user.

Systems and processes for multilingual word prediction are provided. In accordance with one example, a method includes, at an electronic device having one or more processors and memory, receiving context information associated with a current word; determining, for each of a plurality of languages, a set of monolingual probabilities based on the context information; determining a set of language weights based on the context information; determining a set of multilingual probabilities based on the respective sets of monolingual probabilities and the set of language weights; and providing a plurality of candidate words based on the set of multilingual probabilities.

An embodiment provides a system (100) and a method (700) for enabling translation of speech is provided. The system includes an application module (104) configured to receive input identifying a first language of an audio input and a second language into which the audio input in the first language is to be translated. The application module (104) determines the availability of at least one human translator capable of translating the first language into the second language and second language into the first language, in at least one database of human translator. Content, in the second language, which has been translated using the audio input in the first language, is received by the application module (104) from the available human translator. Machine translated content in the second language is received by the application module (104) if the at least one human translator is unavailable.

A method for conducting a cross lingual searching utilizing an ontology reference process to ensure thoroughness. When a query is entered, an ontology database is accessed to identify all representations for the parent entity of interest within specified languages. These representations are used to form a search set that results in more thorough collection from the data sources. Thus, the disclosed method accommodates situations where languages do not follow the same construct (e.g. English compared to Chinese) and where direct translation does not adequately represent the intent of the user's inquiry.