This application relates to a systems and methods for trending issue identification in text streams. In one embodiment, a method for improving resolution of a trending issue identified in a set of text streams includes presenting a user interface of an application that is being executed by a computing device. The method also includes receiving a notification including the trending issue that has been identified in the set of text streams based at least in part on textual analysis performed on the set of text streams, and presenting the trending issue on the user interface of the application to enable an action to be performed to resolve the trending issue.

This application relates to a systems and methods for trending issue identification in text streams. In one embodiment, a method for improving resolution of a trending issue identified in a set of text streams includes presenting a user interface of an application that is being executed by a computing device. The method also includes receiving a notification including the trending issue that has been identified in the set of text streams based at least in part on textual analysis performed on the set of text streams, and presenting the trending issue on the user interface of the application to enable an action to be performed to resolve the trending issue.

A computer implemented method includes receiving a natural language utterance, generating multiple alternative N-gram contexts for a evaluating a next word in the natural language utterance, selecting N-gram context candidates from the multiple alternative N-gram contexts comprising different sets of N-1 words in the natural language utterance for selecting a next word in the natural language utterance, and providing the N-gram context candidates for creating a transcript of the natural language utterance.

A computer implemented method includes receiving a natural language utterance, generating multiple alternative N-gram contexts for a evaluating a next word in the natural language utterance, selecting N-gram context candidates from the multiple alternative N-gram contexts comprising different sets of N-1 words in the natural language utterance for selecting a next word in the natural language utterance, and providing the N-gram context candidates for creating a transcript of the natural language utterance.

Embodiments described herein provides a contrastive learning framework that leverages hard negative examples, that are mined globally from the entire training corpus for a given query to improve the quality of code and natural language representations. Specifically, similar examples from the training corpus are extracted and used as hard negatives in an online manner during training while keeping the minibatch construction random.

Embodiments described herein provides a contrastive learning framework that leverages hard negative examples, that are mined globally from the entire training corpus for a given query to improve the quality of code and natural language representations. Specifically, similar examples from the training corpus are extracted and used as hard negatives in an online manner during training while keeping the minibatch construction random.

An electronic apparatus which acquires input data to be input into a TTS module for outputting a voice through the TTS module, acquires a voice signal corresponding to the input data through the TTS module, detects an error in the acquired voice signal based on the input data, corrects the input data based on the detection result, and acquires a corrected voice signal corresponding to the corrected input data through the TTS module.

The present disclosure relates to determining the reliability of online content items using a non-linear data structure. More particularly, the present invention provides an effective tool for slowing down the spread of false or unreliable content online using a non-linear data structure. The present disclosure provides an algorithm that leverages content items available within the wider ecosystem associated with a root note to determine a content item's level of accuracy or reliability based on what is currently known about a topic or event associated with the content item.

Methods and systems to automatically construct a clinical study site visit report (SVR), conduct the SVR, evaluate the SVR in real-time, and provide feedback while the SVR is being conducted. Responses to the SVR include user-selectable answers and natural language notes. Each response is evaluated as it is submitted based on a combination of pre-configured rules and a computer-trained model. If an anomaly is detected and is not already captured in the SVR, an alert is generated during performance of the SVR. The alert may include recommended remedial action.

Secure communication in mobile digital pages is provided. The system receives an electronic document and validates the electronic document for storage in a cache server. The system receives a request for the electronic document and provides it to a viewer component on a client computing device. The viewer component loads the electronic document in an iframe. The viewer component executes a runtime component to receive, via a secure communication channel, a tag from the electronic document. The system receives the tag and selects a data value for transmission to the viewer component. The viewer components provides the data value to cause the runtime component to execute an action with the data value.