The present disclosure provides systems and methods that leverage machine-learned models (e.g., neural networks) to provide enhanced communication assistance. In particular, the systems and methods of the present disclosure can include or otherwise leverage a machine-learned communication assistance model to detect problematic statements included in a communication and/or provide suggested replacement statements to respectively replace the problematic statements. In one particular example, the communication assistance model can include a long short-term memory recurrent neural network that detects an inappropriate tone or unintended meaning within a user-composed communication and provides one or more suggested replacement statements to replace the problematic statements.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer-implemented method for communication assistance, the method comprising: receiving, by one or more computing devices, a first communication provided by a user; providing, by the one or more computing devices, a first set of sequential communication data descriptive of the first communication provided by the user for input into a machine-learned communication assistance model, wherein the machine-learned communication assistance model comprises at least one long short-term memory recurrent neural network; receiving, by the one or more computing devices, one or more indications that respectively identify one or more problematic statements included in the first communication, the one or more indications output by the machine-learned communication assistance model; and providing, by the one or more computing devices, information regarding the one or more problematic statements for display to the user. 2. The computer-implemented method of claim 1, wherein providing, by the one or more computing devices, the first set of sequential communication data for input into the machine-learned communication assistance model comprises providing, by the one or more computing devices, a string of text for input into the machine-learned communication assistance model, the string of text input into the machine-learned communication assistance model according to an order of user entry associated with the string of text. 3. The computer-implemented method of claim 1, further comprising: receiving, by the one or more computing devices, one or more suggested replacement statements to respectively replace the one or more problematic statements, the one or more suggested replacement statements output by the machine-learned communication assistance model; wherein providing, by the one or more computing devices, the information regarding the one or more problematic statements for display to the user comprises providing, by the one or more computing devices, the one or more suggested replacement statements for display to the user. 4. The computer-implemented method of claim 1, wherein receiving, by the one or more computing devices, the one or more indications that respectively identify the one or more problematic statements included in the first communication comprises receiving, by the one or more computing devices, the one or more indications that respectively identify the one or more problematic statements that have an inappropriate tone relative to an intended recipient of the first communication. 5. The computer-implemented method of claim 1, wherein receiving, by the one or more computing devices, the one or more indications that respectively identify the one or more problematic statements included in the first communication comprises receiving, by the one or more computing devices, the one or more indications that respectively identify the one or more problematic statements that respectively include one or more of: offensive language, confidential information, or legally problematic statements. 6. The computer-implemented method of claim 1, further comprising: receiving, by the one or more computing devices, one or more suggested replacement statements to respectively replace the one or more problematic statements, the one or more suggested replacement statements output by the machine-learned communication assistance model; wherein providing, by the one or more computing devices, information regarding the one or more problematic statements for display to the user comprises automatically replacing, by the one or more computing devices, the one or more problematic statements in the first communication with the one or more suggested replacement statements. 7. The computer-implemented method of claim 1, wherein providing, by the one or more computing devices, information regarding the one or more problematic statements for display to the user comprises providing, by the one or more computing devices, a notification for display within a user interface, wherein the notification indicates the existence of the one or more problematic statements. 8. A computing system to provide communication assistance, the computing system comprising: at least one processor; a machine-learned communication assistance model that comprises at least one recurrent neural network, wherein the communication assistance model is trained to receive a first set of sequential communication data descriptive of a first communication provided by a user and, in response to receipt of the first set of sequential communication data, detect one or more problematic statements included in the first communication; and at least one tangible, non-transitory computer-readable medium that stores instructions that, when executed by the at least one processor, cause the at least one processor to: obtain the first set of sequential communication data descriptive of the first communication provided by the user; input the first set of sequential communication data into the communication assistance model; and receive, as an output of the communication assistance model, one or more indications that respectively identify the one or more problematic statements included in the first communication. 9. The computing system of claim 8, wherein the one or more problematic statements include one or more of: an inappropriate tone, offensive language, confidential information, or legally problematic statements. 10. The computing system of claim 8, wherein: the instructions that cause the at least one processor to input the first set of sequential communication data into the communication assistance model cause the at least one processor to input the first set of sequential communication data into the recurrent neural network of the communication assistance model; and the recurrent neural network outputs the one or more indications. 11. The computing system of claim 10, wherein the recurrent neural network comprises a long short-term memory recurrent neural network. 12. The computing system of claim 8, wherein: the communication assistance model comprises a feature extraction component; the instructions that cause the at least one processor to input the first set of sequential communication data into the communication assistance model cause the at least one processor to input the first set of sequential communication data into the feature extraction component; the feature extraction component extracts one or more features of the first communication; and the communication assistance model outputs the one or more indications based at least in part on the one or more features extracted by the feature extraction component. 13. The computing system of claim 8, wherein the communication assistance model outputs, for each of the one or more problematic statements, at least one confidence score for at least one of a plurality of categories of problematic statements. 14. The computing system of claim 13, wherein execution of the instructions further causes the computing system to select one of a plurality of different interventions based at least in part on the at least one confidence score, wherein each of the plurality of different interventions alerts the user to the existence of the one or more problematic statements, and wherein the plurality of different interventions have different amounts of intrusiveness. 15. The computing system of claim 8, wherein: the communication assistance model comprises a context component and a machine-learned detection model; execution of the instructions further causes the at least one processor to input information about the user and an intended recipient of the first communication into the context component; in response to receipt of the information about the user and the intended recipient of the first communication, the context component outputs a context categorization that describes an appropriate tone for the first communication; the machine-learned detection model outputs the one or more indications based at least in part on the context categorization output by the context component. 16. The computing system of claim 8, wherein the communication assistance model comprises a replacement portion that provides one or more suggested replacement statements to respectively replace the one or more problematic statements. 17. The computing system of claim 16, wherein the replacement portion comprises a machine-learned machine-translation model. 18. A user computing device, the user computing device comprising: at least one processor; and at least one non-transitory computer-readable medium that stores instructions that, when executed by the at least one processor, cause the user computing device to: receive a first communication provided by a user; provide a first set of communication data descriptive of the first communication provided by the user for input into a machine-learned communication assistance model, wherein the machine-learned communication assistance model comprises at least one long short-term memory recurrent neural network; receive one or more indications that respectively identify one or more problematic statements included in the first communication, the one or more indications output by the machine-learned communication assistance model; and display a notification that indicates the existence of the one or more problematic statements. 19. The user computing device of claim 18, wherein the at least one non-transitory computer-readable medium of the user computing device stores the machine-learned communication assistance model. 20. The user computing device of claim 18, wherein the execution of the instructions further causes the user computing device to: receive one or more suggested replacement statements to respectively replace the one or more problematic statements, the one or more suggested replacement statements output by the machine-learned communication assistance model; and display the one or more suggested replacement statements.