Servicenow, Inc.

Oracle International Corporation

Ankit Goel

Jebakumar Mathuram Santhosm Swvigaradoss

Rajesh Voleti

Rishabh Verma

Satya Sarika Sunkara

Prashant Pandey

John Alan Botica

Laxmi Prasanna Mustala

Jebakumar Mathuram Santhosam Swvigaradoss

Jason Douglas Aloia

Patrick Casey

Samantha Santo

Michael Dominic Malcangio

Srikar Bakka

Deepak Garg

Rao Subrahmanyeswara Surapaneni

Thomas Hora

Sunitha Alli

Sunitha Mukka

Arjun Hegde

Rao Surapaneni

Data indicative of one or more user inputs directed to a user interface of a conversation designer tool is received. A conversation design is determined based on the data. The conversation design enables a conversation bot to provide a service using a conversation flow specified at least in part by the conversation design. The conversation design specifies in a first human language at least a portion of a message content to be provided by the conversation bot during an execution of the conversation flow. It is identified that an end-user of the conversation bot prefers to converse in a second human language different from the first human language. The message content of the conversation design in the first human language is dynamically translated for the end-user to the second human language.

Dynamic translation for a conversation

One or more associated identifiers are determined based on one or more associated tag types of an interactable element of web content. The determined one or more associated identifiers are associated with the interactable element. Based on the association of the determined one or more associated identifiers with the interactable element, one of the interactable element is matched to a received speech input. An action is performed with respect to the interactable element based on the matching.

Enabling speech interactions on web-based user interfaces

A conversation design is received for a conversation bot that enables the conversation bot to provide a service using a conversation flow specified at least in part by the conversation design. The conversation design specifies in a first human language at least a portion of a message content to be provided by the conversation bot. It is identified that an end-user of the conversation bot prefers to converse in a second human language different from the first human language. In response to a determination that the message content is to be provided by the conversation bot to the end-user, the message content of the conversation design is dynamically translated for the end-user from the first human language to the second human language. The translated message content is provided to the end-user in a message from the conversation bot.

An embodiment may involve a database containing a first user profile that specifies a first preferred language of a first user and a second user profile that specifies a second preferred language of a second user. The embodiment may also involve one or more processors configured to: receive, from the first user and within a chat session, a first set of messages in the first preferred language; cause the first set of messages to be translated into the second preferred language; provide, to the second user and within the chat session, the first set of messages as translated; receive, from the second user and within the chat session, a second set of messages in the second preferred language; cause the second set of messages to be translated into the first preferred language; and provide, to the first user and within the chat session, the second set of messages as translated.

Machine translation of chat sessions

An example embodiment may involve a software application executable on computing devices of a remote network management platform containing a computational instance associated with a managed network. A text string may be received, and characters of the string may be categorized among a plurality of symbol script families. A respective likelihood of the string corresponding to each family may be determined, and a respective probability of the string being in each language of each given family may also be determined. The respective probabilities for the languages of each given family may be weighted by the likelihoods of the given family, and then weighted sums of the probabilities for each language may be computed. The maximum of the weighted sums may correspond to the language of the text string. The respective probabilities may be determined according to hybrid N-gram and word language models for each family.

Hybrid language detection model

Web content with a speech interaction user interface capability is provided. Interactable elements of the web content are identified. For each of the interactable elements, one or more associated identifiers are determined and associated with a corresponding interactable element of the identified interactable elements in a data structure. A speech input is received from a user. Using the data structure, one of the interactable elements is matched to the received speech input. An action is automatically performed on the matched interactable element.

A database may contain text strings in a preferred language and in one or more other languages. One or more processors may be configured to: generate a graphical user interface containing the text strings in the preferred language and in the other languages, and a control for dynamic translation, wherein a first set of the text strings in the other languages are displayed within text input controls, and wherein a second set of the text strings in the other languages are not displayed within the text input controls; receive an activation indication of the control for dynamic translation; and generate an update to the graphical user interface that includes translations of the first set into the preferred language appearing adjacent to the first set in the other languages, and also translations of the second set into the preferred language replacing the second set in the other languages.

Dynamic translation of graphical user interfaces

The present disclosure relates generally to dynamic translation of text and/or audio data. The client instance hosted by one or more data centers and accessible by one or more remote client networks. In accordance with the present approach, a translation request is received from a user via a client device, wherein the translation request is associated with an untranslated file and a target language. Further, a source language of the untranslated file is identified. Further still, the untranslated file and the target language are outputted to a third party translation service. Even further, a translated file based on the target language, the untranslated file and a source language of the untranslated file is received.

Dynamic translation

This disclosure describes, generally, methods and systems for implementing application agnostic UI integration. Aspects of the invention relates to a generic architecture and a framework, which leverage the capabilities of a middleware server and application integration concepts, to support launching a User Interface (UI) of any target application from any source application. The source application can invoke, for example, a HTTP get request or fires a HTTP post to the target application, and the same interaction can take place while returning control back from target application to source application. Additionally, the target application can invoke a service hosted on the source application to return the control back to source application.

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Hyderabad Telangana, India

Ankit Goel