Abstract: A computer-implemented process is programmed to programmatically receive, using a first computer system, electronic digital data representing input time-correlated speech data and video data, determine a first text sequence corresponding to the input time-correlated speech data, the first text sequence comprising unstructured natural language text, determining syntactic structure data associated with the first text sequence, inputting the time-correlated video data and the syntactic structure data associated with the first text sequence into one or more machine learning models, the machine learning models producing an output of one or more scores for at least a portion of the time-correlated video data and first text sequence, transforming the output of one or more scores to yield and output set of summary points and suggestions, and transmitting a graphical element of the output set of summary points and suggestions for display.

Abstract: In an embodiment, a programmed computer system implemented via client-server Software as a Service (SaaS) techniques provides an interactive user interface for identifying specific portions of a digital document susceptible for review and improvement. A server computer may receive a representation of a digital document, such as an email, comprising words arranged into sentences arranged into paragraphs. An embodiment may tokenize a set of all sentences comprising the sequence of sentences into a document-specific vocabulary, then compute a corresponding first and second score for each sentence of the sequence of sentences. The first score may represent a calculated probability of semantic importance of the corresponding sentence to an overall meaning of the digital document. The second score may represent a calculated likelihood that the corresponding sentence will be read by a future reader of the digital document. An embodiment may identify key sentences using the first scores and second scores.

Abstract: In an embodiment, a programmed computer system implemented via client-server Software as a Service (SaaS) techniques provides an interactive user interface for identifying specific portions of a digital document susceptible for review and improvement. A server computer may receive a representation of a digital document, such as an email, comprising words arranged into sentences arranged into paragraphs. An embodiment may tokenize a set of all sentences comprising the sequence of sentences into a document-specific vocabulary, then compute a corresponding first and second score for each sentence of the sequence of sentences. The first score may represent a calculated probability of semantic importance of the corresponding sentence to an overall meaning of the digital document. The second score may represent a calculated likelihood that the corresponding sentence will be read by a future reader of the digital document. An embodiment may identify key sentences using the first scores and second scores.