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公开(公告)号：US20210266407A1
公开(公告)日：2021-08-26
申请号：US16903082
申请日：2020-06-16
Applicant: SAP SE
Inventor： Anh Burton , Hans-Martin Will , James Tian , Andreas Kurt Pursche , Jeff Dixon , Matthew Berg , Thomas Obermeyer
Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives a set of audio files. Each audio file in the set of audio files includes audio from an audio call. The program further truncates each audio file in the set of audio files to a defined call length. For each audio call in the set of audio calls, the program also receives a transcript of the audio call based on the audio file of the audio call. For each audio call in the set of audio calls, the program further uses the transcript of the audio call as input to a machine learning model for the machine learning model to predict a category from a plurality of categories that is associated with the audio call.
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公开(公告)号：US12192409B2
公开(公告)日：2025-01-07
申请号：US16903082
申请日：2020-06-16
Applicant: SAP SE
Inventor： Anh Burton , Hans-Martin Will , James Tian , Andreas Kurt Pursche , Jeff Dixon , Matthew Berg , Thomas Obermeyer
IPC: H04M3/00 , G06N20/00 , G06Q30/016 , G10L15/26 , H04M3/523
Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives a set of audio files. Each audio file in the set of audio files includes audio from an audio call. The program further truncates each audio file in the set of audio files to a defined call length. For each audio call in the set of audio calls, the program also receives a transcript of the audio call based on the audio file of the audio call. For each audio call in the set of audio calls, the program further uses the transcript of the audio call as input to a machine learning model for the machine learning model to predict a category from a plurality of categories that is associated with the audio call.
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公开(公告)号：US20230096720A1
公开(公告)日：2023-03-30
申请号：US17486126
申请日：2021-09-27
Applicant: SAP SE
Inventor： Martin Wezowski , Hans-Martin Will , Rohit Jalagadugula , Kavitha Krishnan , Sai Hareesh Anamandra , Vinay George Roy , Parthasarathy Menon , Alexander Schaefer
IPC: G06Q10/06
Abstract: A method may include collecting data from a variety of data sources associated with a user. The data sources may include personal data sources, corporate data sources, and public data source. The data collected from the variety of data sources may be enriched through categorization and aggregation. For example, browser history may be categorized based on types of website and aggregated to reflect the quantity of interactions with each category of website. A multi-dimensional digital profile may be generated based on the enriched data. For instance, the digital profile may include a social, emotional, spiritual, environmental, occupational, intellectual, and physical dimension. One or more recommendation corresponding to one or more of a burnout prediction, wellness recommendation, learning plan, skill gap, and personality type may be generated based on the digital profile. Related systems and computer program products are also provided.
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公开(公告)号：US11853950B2
公开(公告)日：2023-12-26
申请号：US17486126
申请日：2021-09-27
Applicant: SAP SE
Inventor： Martin Wezowski , Hans-Martin Will , Rohit Jalagadugula , Kavitha Krishnan , Sai Hareesh Anamandra , Vinay George Roy , Parthasarathy Menon , Alexander Schaefer
IPC: G06Q10/0639 , G06Q10/067 , G06Q10/0633 , H04L67/50
CPC classification number: G06Q10/06398 , G06Q10/067 , G06Q10/0633 , H04L67/535
Abstract: A method may include collecting data from a variety of data sources associated with a user. The data sources may include personal data sources, corporate data sources, and public data source. The data collected from the variety of data sources may be enriched through categorization and aggregation. For example, browser history may be categorized based on types of website and aggregated to reflect the quantity of interactions with each category of website. A multi-dimensional digital profile may be generated based on the enriched data. For instance, the digital profile may include a social, emotional, spiritual, environmental, occupational, intellectual, and physical dimension. One or more recommendation corresponding to one or more of a burnout prediction, wellness recommendation, learning plan, skill gap, and personality type may be generated based on the digital profile. Related systems and computer program products are also provided.
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