Abstract: Text coherence is classified by receiving a multiword text string into a machine learning model, determining, by the machine learning model, semantic probability data representing a probability that a word of the received multiword text string is semantically correlated to one or more other words in the multiword text string, determining, by the machine learning model, an inferential aggregate perplexity score of the multiword text string, based on the determined semantic probability data, outputting, from the machine learning model, the inferential aggregate perplexity score, and classifying a coherence of the multiword text string based on whether the outputted inferential aggregate perplexity score satisfies a coherence condition, wherein the coherence condition is based on a predefined coherence score.

Abstract: A method of generating keyword-based dialogue summaries is provided. The method includes inputting a transcript of an audio conversation and a keyword into a machine learning model trained based on encodings representing the keyword and the transcript, generating computer-generated text different from and semantically descriptive of the transcript and semantically associated with the keyword, and outputting the computer-generated text in association with a selectable item selectable for inclusion of the computer-generated text in displayed text representing the transcript, the selectable item associated with the keyword.