Selective text prediction for electronic messaging

2:

• The method of claim 1, wherein predicting the first candidate portion of text comprises:
• predicting, by the computing system and using a machine learning model, one or more candidate portions of text to follow the first portion of text, the one or more candidate portions of text including the first candidate portion of text, wherein the first candidate portion of text includes a token;
• and
• modifying the first candidate portion of text to generate a modified first candidate portion of text by replacing the token with text determined based on one or both of context of the electronic message or information about a user editing the electronic message,
• wherein outputting the predicted first candidate portion of text comprises outputting, for display, the modified first candidate portion of text.

3:

• The method of claim 2, further comprising:
• receiving a corpus of text;
• modifying the corpus of text to generate a modified corpus of text by replacing fields in the corpus with corresponding tokens;
• and
• training the machine learning model using the modified corpus of text.

8:

• A computing system comprising:
• one or more user interface components configured to receive typed user input;
• and
• one or more processors configured to:
• receive, by a computing system and at a first time, a first portion of text typed by a user in an electronic message being edited;
• predict, based on the first portion of text, a first candidate portion of text to follow the first portion of text;
• output, for display, the predicted first candidate portion of text for optional selection to append to the first portion of text;
• determine, at a second time that is after the first time and based on a modification to the electronic message performed between the first time and the second time, that the electronic message is directed to a sensitive topic;
• and
• responsive to determining that the electronic message is directed to a sensitive topic, refrain from outputting subsequent candidate portions of text for optional selection to append to text in the electronic message.

9:

• The computing system of claim 8, wherein, to predict the first candidate portion of text, the one or more processors are configured to:
• predict, using a machine learning model, one or more candidate portions of text to follow the first portion of text, the one or more candidate portions of text including the first candidate portion of text, wherein the first candidate portion of text includes a token;
• and
• modify the first candidate portion of text to generate a modified first candidate portion of text by replacing the token with text determined based on one or both of context of the electronic message or information about a user editing the electronic message,
• wherein, to output the predicted first candidate portion of text, the one or more processors are configured to output, for display, the modified first candidate portion of text.

10:

• The computing system of claim 9, wherein the one or more processors are further configured to:
• receive a corpus of text;
• modify the corpus of text to generate a modified corpus of text by replacing fields in the corpus with corresponding tokens;
• and
• train the machine learning model using the modified corpus of text.

15:

• A computer-readable storage medium storing instructions that, when executed, cause one or more processors of a computing system to:
• receive, at a first time, a first portion of text of an electronic message being edited;
• predict, based on the first portion of text, a first candidate portion of text to follow the first portion of text;
• output, for display, the predicted first candidate portion of text for optional selection to append to the first portion of text;
• determine, at a second time that is after the first time and based on a modification to the electronic message performed between the first time and the second time, that the electronic message is directed to a sensitive topic;
• and
• responsive to determining that the electronic message is directed to a sensitive topic, refrain from outputting subsequent candidate portions of text for optional selection to append to text in the electronic message.

16:

• The computer-readable storage medium of claim 15, wherein the instructions that cause the one or more processors to predict the first candidate portion of text comprise instructions that cause the one or more processors to:
• predict, using a machine learning model, one or more candidate portions of text to follow the first portion of text, the one or more candidate portions of text including the first candidate portion of text, wherein the first candidate portion of text includes a token;
• and
• modify the first candidate portion of text to generate a modified first candidate portion of text by replacing the token with text determined based on one or both of context of the electronic message or information about a user editing the electronic message,
• wherein the instructions that cause the one or more processors to output the predicted first candidate portion of text comprise instructions that cause the one or more processors to output, for display, the modified first candidate portion of text.

17:

• The computer-readable storage medium of claim 16, further comprising instructions that cause the one or more processors to:
• receive a corpus of text;
• modify the corpus of text to generate a modified corpus of text by replacing fields in the corpus with corresponding tokens;
• and
• train the machine learning model using the modified corpus of text.