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公开(公告)号：US10522152B2
公开(公告)日：2019-12-31
申请号：US16170278
申请日：2018-10-25
Applicant: Verint Systems Ltd.
Inventor： Omer Ziv , Ran Achituv , Ido Shapira , Jeremie Dreyfuss
Abstract: Systems and methods of diarization using linguistic labeling include receiving a set of diarized textual transcripts. A least one heuristic is automatedly applied to the diarized textual transcripts to select transcripts likely to be associated with an identified group of speakers. The selected transcripts are analyzed to create at least one linguistic model. The linguistic model is applied to transcripted audio data to label a portion of the transcripted audio data as having been spoken by the identified group of speakers. Still further embodiments of diarization using linguistic labeling may serve to label agent speech and customer speech in a recorded and transcripted customer service interaction.
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公开(公告)号：US20190066690A1
公开(公告)日：2019-02-28
申请号：US16170278
申请日：2018-10-25
Applicant: Verint Systems Ltd.
Inventor： Omer Ziv , Ran Achituv , Ido Shapira , Jeremie Dreyfuss
Abstract: Systems and methods of diarization using linguistic labeling include receiving a set of diarized textual transcripts. A least one heuristic is automatedly applied to the diarized textual transcripts to select transcripts likely to be associated with an identified group of speakers. The selected transcripts are analyzed to create at least one linguistic model. The linguistic model is applied to transcripted audio data to label a portion of the transcripted audio data as having been spoken by the identified group of speakers. Still further embodiments of diarization using linguistic labeling may serve to label agent speech and customer speech in a recorded and transcripted customer service interaction.
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公开(公告)号：US09875743B2
公开(公告)日：2018-01-23
申请号：US15006575
申请日：2016-01-26
Applicant: Verint Systems Ltd.
Inventor： Alex Gorodetski , Ido Shapira , Ron Wein , Oana Sidi
IPC: G10L15/00 , G10L15/06 , G10L17/00 , G10L17/20 , G10L17/04 , G10L17/16 , G10L17/02 , G10L25/84 , G10L15/26
Abstract: Disclosed herein are methods of diarizing audio data using first-pass blind diarization and second-pass blind diarization that generate speaker statistical models, wherein the first pass-blind diarization is on a per-frame basis and the second pass-blind diarization is on a per-word basis, and methods of creating acoustic signatures for a common speaker based only on the statistical models of the speakers in each audio session.
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公开(公告)号：US09633650B2
公开(公告)日：2017-04-25
申请号：US14291893
申请日：2014-05-30
Applicant: Verint Systems Ltd.
Inventor： Ran Achituv , Omer Ziv , Roni Romano , Ido Shapira , Daniel Baum
IPC: G10L15/26 , G10L15/065 , G06F17/30 , G10L15/07 , G10L15/08
CPC classification number: G10L15/065 , G06F17/30746 , G10L15/01 , G10L15/07 , G10L15/083 , G10L15/14 , G10L15/26
Abstract: Methods, systems, and computer readable media for automated transcription model adaptation includes obtaining audio data from a plurality of audio files. The audio data is transcribed to produce at least one audio file transcription which represents a plurality of transcription alternatives for each audio file. Speech analytics are applied to each audio file transcription. A best transcription is selected from the plurality of transcription alternatives for each audio file. Statistics from the selected best transcription are calculated. An adapted model is created from the calculated statistics.
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公开(公告)号：US20170098445A1
公开(公告)日：2017-04-06
申请号：US15332411
申请日：2016-10-24
Applicant: Verint Systems Ltd.
Inventor： Ran Achituv , Omer Ziv , Ido Shapira , Daniel Baum
IPC: G10L15/197 , G10L15/08 , G10L15/06
CPC classification number: G10L15/197 , G06F17/30746 , G10L15/063 , G10L15/083 , G10L15/26 , G10L2015/0635 , H04M3/51
Abstract: Systems and methods of automated adaptation of a language model for transcription of audio data include obtaining audio data. The audio data is transcribed with a language model to produce a plurality of audio tile transcriptions. A quality of the plurality of audio file transcriptions is evaluated. At least one best transcription from a plurality of audio tile transcriptions is selected based upon the evaluated quality. Statistics are calculated from the selected at least one best transcription from the plurality of audio file transcriptions. The language model is modified from the calculated statistics.
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Patent Agency Ranking
公开(公告)号：US10720164B2
公开(公告)日：2020-07-21
申请号：US16702998
申请日：2019-12-04
Applicant: Verint Systems Ltd.
Inventor： Omer Ziv , Ran Achituv , Ido Shapira , Jeremie Dreyfuss
Abstract: Systems and methods of diarization using linguistic labeling include receiving a set of diarized textual transcripts. A least one heuristic is automatedly applied to the diarized textual transcripts to select transcripts likely to be associated with an identified group of speakers. The selected transcripts are analyzed to create at least one linguistic model. The linguistic model is applied to transcripted audio data to label a portion of the transcripted audio data as having been spoken by the identified group of speakers. Still further embodiments of diarization using linguistic labeling may serve to label agent speech and customer speech in a recorded and transcripted customer service interaction.
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公开(公告)号：US10650826B2
公开(公告)日：2020-05-12
申请号：US16594812
申请日：2019-10-07
Applicant: Verint Systems Ltd.
Inventor： Omer Ziv , Ran Achituv , Ido Shapira , Jeremie Dreyfuss
Abstract: Systems and method of diarization of audio files use an acoustic voiceprint model. A plurality of audio files are analyzed to arrive at an acoustic voiceprint model associated to an identified speaker. Metadata associate with an audio file is used to select an acoustic voiceprint model. The selected acoustic voiceprint model is applied in a diarization to identify audio data of the identified speaker.
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公开(公告)号：US20200105275A1
公开(公告)日：2020-04-02
申请号：US16702998
申请日：2019-12-04
Applicant: Verint Systems Ltd.
Inventor： Omer Ziv , Ran Achituv , Ido Shapira , Jeremie Dreyfuss
Abstract: Systems and methods of diarization using linguistic labeling include receiving a set of diarized textual transcripts. A least one heuristic is automatedly applied to the diarized textual transcripts to select transcripts likely to be associated with an identified group of speakers. The selected transcripts are analyzed to create at least one linguistic model. The linguistic model is applied to transcripted audio data to label a portion of the transcripted audio data as having been spoken by the identified group of speakers. Still further embodiments of diarization using linguistic labeling may serve to label agent speech and customer speech in a recorded and transcripted customer service interaction.
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公开(公告)号：US10593332B2
公开(公告)日：2020-03-17
申请号：US16567446
申请日：2019-09-11
Applicant: Verint Systems Ltd.
Inventor： Omer Ziv , Ran Achituv , Ido Shapira , Jeremie Dreyfuss
Abstract: Systems and methods diarization using linguistic labeling include receiving a set of diarized textual transcripts. A least one heuristic is automatedly applied to the diarized textual transcripts to select transcripts likely to be associated with an identified group of speakers. The selected transcripts are analyzed to create at least one linguistic model. The linguistic model is applied to transcripted audio data to label a portion of the transcripted audio data as having been spoken by the identified group of speakers. Still further embodiments of diarization using linguistic labeling may serve to label agent speech and customer speech in a recorded and transcripted customer service interaction.
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公开(公告)号：US20190066691A1
公开(公告)日：2019-02-28
申请号：US16170289
申请日：2018-10-25
Applicant: Verint Systems Ltd.
Inventor： Omer Ziv , Ran Achituv , Ido Shapira , Jeremie Dreyfuss
Abstract: Systems and methods of diarization using linguistic labeling include receiving a set of diarized textual transcripts. A least one heuristic is automatedly applied to the diarized textual transcripts to select transcripts likely to be associated with an identified group of speakers. The selected transcripts are analyzed to create at least one linguistic model. The linguistic model is applied to transcripted audio data to label a portion of the transcribed audio data as having been spoken by the identified group of speakers. Still further embodiments of diarization using linguistic labeling may serve to label agent speech and customer speech in a recorded and transcripted customer service interaction.
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