Abstract: Handling multi-loop feedback for machine learning model (MLM) pipelines may be provided by receiving annotations regarding an analysis output of the MLM for a recorded natural language conversation, wherein the annotations include at least a first and second corrections to corresponding first and second errors in the analysis output; identifying, corresponding first and second sub-models of the plurality of sub-models that are responsible for the respective first and second errors, wherein the first sub-model occurs earlier in the sequential pipeline than the second sub-model; determining whether the second sub-model, when provided with a first corrected output from the first sub-model based on the first correction produces the second correction as part of a second corrected output from the second model; and in response to determining that the second model produces the second corrected output, retraining only the first sub-model based on the first correction.

Abstract: Artificial intelligence assisted editing may be provided by providing, via a Graphical User Interface (GUI), a transcript of a natural language conversation and a summary of the natural language conversation based on the transcript generated by a machine learning model; in response to receiving user selection of a selected phrase in the transcript or summary, providing an edit interface in the GUI; querying the machine learning model for a suggested phrase to replace the selected phrase with; and populating the edit interface with the suggested phrase.

Abstract: Handling multi-loop feedback for machine learning model pipelines may be provided by providing a review graphical user interface (GUI) including an analysis output, generated by a machine learning model, of a natural language conversation, the analysis output including a transcript and a summary of the natural language conversation based on the transcript; identifying a first candidate phrase and a second candidate phrase in the analysis output; emphasizing the first candidate phrase in the review GUI; in response to receiving a review action in relation to the first candidate phrase: deemphasizing the first candidate phrase; and emphasizing the second candidate phrase in the review GUI.

Abstract: Surfacing supplemental information may be provided by analyzing a transcript of a conversation, by a Natural Language Processing (NLP) system, to identify at least one candidate term in the conversation to provide supplemental information for to a reader of the transcript; in response to receiving, from the reader, a selection of the candidate term, formatting a query that includes the candidate term; in response to receiving a reply to the query: summarizing the reply into an explanation in a human-readable format; and outputting the explanation to the reader.

Abstract: Automating follow-up actions from conversations may be provided by analyzing a transcript of a conversation, by a Natural Language Processing (NLP) system, to generate a summary of the conversation in a human-readable format, the summary including action items associated with an identified entity; retrieving, by the NLP system from a supplemental data source, supplemental data associated with the action item that are lacking in the transcript; generating, by the NLP system, a machine-readable message based on the action item and the supplemental data; and transmitting the machine-readable message to a system associated with the identified entity.

Abstract: A user interface (UI) linking analyzed segments of transcripts with extracted key points may be provided by capturing audio of a conversation including first and second pluralities of utterances respectively spoken by first and second parties; transmitting the audio to a Natural Language Processing (NLP) system; receiving a transcript of the conversation and analysis outputs from the transcript including a key point and hyperlink to a most-semantically-relevant segment of a plurality of segments included in the transcript for the key point according to a semantic context for the key point within the conversation; displaying, in a UI, the transcript and a selectable representation of the key point; and in response to receiving a selection of the selectable representation via the UI, adjusting display of the transcript in the UI to highlight the most-semantically-relevant segment.