DYNAMIC SUMMARY ADJUSTMENTS FOR LIVE SUMMARIES

Abstract: described techniques may be utilized to process transcribed text of a transcription stream using a compression ratio machine learning (ml) model to determine at least two compression ratios. the transcribed text may then be processed by a summarization ml model using the at least two compression ratios to obtain a summary stream that includes first summarized text having a first compression ratio of the at least two compression ratios, relative to a first corresponding portion of the transcribed text, and second summarized text having a second compression ratio of the at least two compression ratios, relative to a second corresponding portion of the transcribed text. the transcribed text may also be summarized by the summarization ml model based on a complexity score determined by a complexity ml model.

Inventor(s): Vikas Bahirwani, Alex Olwal, Ruofei Du, Manish Gupta, Susan Xu

CPC Classification: G06F40/47 (ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models ))

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