1. A method comprising: receiving domain-specific training data of sentences describing a target entity in a context; extracting a speaker history and a visual context from the domain-specific training data; selecting attributes of the target entity based on at least one of the speaker history, the visual context, and speaker preferences; generating a text expression referring to the target entity based on at least one of the attributes, the speaker history, and the context; and outputting, via a processor, the text expression.
1. A method comprising: receiving domain-specific training data of sentences describing a target entity in a context; extracting a speaker history and a visual context from the domain-specific training data; selecting attributes of the target entity based on at least one of the speaker history, the visual context, and speaker preferences; generating a text expression referring to the target entity based on at least one of the attributes, the speaker history, and the context; and outputting, via a processor, the text expression. 4. The method of claim 1 , wherein generating the text expression is further based on a permute and order model.