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    Data driven speech enabled self-help systems and methods of operating thereof
    21.
    发明授权
    Data driven speech enabled self-help systems and methods of operating thereof 有权

    公开(公告)号：US10515150B2

    公开(公告)日：2019-12-24

    申请号：US14799369

    申请日：2015-07-14

    Applicant: GENESYS TELECOMMUNICATIONS LABORATORIES, INC.

    Inventor： Yoni Lev ,  Tamir Tapuhi ,  Avraham Faizakof ,  Amir Lev-Tov ,  Yochai Konig

    IPC: G06F17/27 ,  G10L15/18

    Abstract: A method for configuring an automated, speech driven self-help system based on prior interactions between a plurality of customers and a plurality of agents includes: recognizing, by a processor, speech in the prior interactions between customers and agents to generate recognized text; detecting, by the processor, a plurality of phrases in the recognized text; clustering, by the processor, the plurality of phrases into a plurality of clusters; generating, by the processor, a plurality of grammars describing corresponding ones of the clusters; outputting, by the processor, the plurality of grammars; and invoking configuration of the automated self-help system based on the plurality of grammars.

    Fast out-of-vocabulary search in automatic speech recognition systems
    23.
    发明授权
    Fast out-of-vocabulary search in automatic speech recognition systems 有权

    公开(公告)号：US10290301B2

    公开(公告)日：2019-05-14

    申请号：US15402070

    申请日：2017-01-09

    Applicant: GENESYS TELECOMMUNICATIONS LABORATORIES, INC.

    Inventor： Amir Lev-Tov ,  Avraham Faizakof ,  Yochai Konig

    IPC: G10L15/02 ,  G10L15/18 ,  G10L15/19 ,  G10L15/30 ,  G06F17/30 ,  G10L15/08

    Abstract: A method including: receiving, on a computer system, a text search query, the query including one or more query words; generating, on the computer system, for each query word in the query, one or more anchor segments within a plurality of speech recognition processed audio files, the one or more anchor segments identifying possible locations containing the query word; post-processing, on the computer system, the one or more anchor segments, the post-processing including: expanding the one or more anchor segments; sorting the one or more anchor segments; and merging overlapping ones of the one or more anchor segments; and searching, on the computer system, the post-processed one or more anchor segments for instances of at least one of the one or more query words using a constrained grammar.

    SYSTEM AND METHOD FOR SEMANTICALLY EXPLORING CONCEPTS
    25.
    发明申请
    SYSTEM AND METHOD FOR SEMANTICALLY EXPLORING CONCEPTS 有权
    用于扫描概念的系统和方法

    公开(公告)号：US20160012818A1

    公开(公告)日：2016-01-14

    申请号：US14327476

    申请日：2014-07-09

    Applicant: Genesys Telecommunications Laboratories, Inc.

    Inventor： Avraham Faizakof ,  Yoni Lev ,  Amir Lev-Tov ,  Yochai Konig

    IPC: G10L15/06 ,  G06F17/30

    CPC classification number: G10L15/063 ,  G06F17/2755 ,  G06F17/2785 ,  G06F17/30598 ,  G06F17/30705 ,  G10L2015/0631 ,  G10L2015/223

    Abstract: A method for detecting and categorizing topics in a plurality of interactions includes: extracting, by a processor, a plurality of fragments from the plurality of interactions; filtering, by the processor, the plurality of fragments to generate a filtered plurality of fragments; clustering, by the processor, the filtered fragments into a plurality of base clusters; and clustering, by the processor, the plurality of base clusters into a plurality of hyper clusters.

    Abstract translation: 用于检测和分类多个交互中的主题的方法包括：由处理器从多个交互中提取多个片段; 由所述处理器对所述多个片段进行过滤以产生经过滤的多个片段; 由处理器将经滤波的片段聚类成多个基本簇; 以及由所述处理器将所述多个基本簇聚类成多个超群集。

    Dialogue flow optimization and personalization
    27.
    发明授权
    Dialogue flow optimization and personalization 有权

    公开(公告)号：US10455088B2

    公开(公告)日：2019-10-22

    申请号：US14919675

    申请日：2015-10-21

    Applicant: GENESYS TELECOMMUNICATIONS LABORATORIES, INC.

    Inventor： Tamir Tapuhi ,  Yochai Konig ,  Amir Lev-Tov ,  Avraham Faizakof ,  Yoni Lev

    IPC: H04M11/00 ,  H04M3/493 ,  H04M3/51 ,  G06F16/332 ,  G10L15/22 ,  H04M7/00

    Abstract: A method for generating a dialog tree for an automated self-help system of a contact center from a plurality of recorded interactions between customers and agents of the contact center includes: computing, by a processor, a plurality of feature vectors, each feature vector corresponding to one of the recorded interactions; computing, by the processor, similarities between pairs of the feature vectors; grouping, by the processor, similar feature vectors based on the computed similarities into groups of interactions; rating, by the processor, feature vectors within each group of interactions based on one or more criteria, wherein the criteria include at least one of interaction time, success rate, and customer satisfaction; and outputting, by the processor, a dialog tree in accordance with the rated feature vectors for configuring the automated self-help system.

    Language model customization in speech recognition for speech analytics
    28.
    发明授权
    Language model customization in speech recognition for speech analytics 有权

    公开(公告)号：US10186255B2

    公开(公告)日：2019-01-22

    申请号：US15247645

    申请日：2016-08-25

    Applicant: Genesys Telecommunications Laboratories, Inc.

    Inventor： Tamir Tapuhi ,  Amir Lev-Tov ,  Avraham Faizakof ,  Yochai Konig

    IPC: G10L15/06 ,  G10L15/26 ,  G06F17/27 ,  G06N99/00 ,  G10L15/08

    Abstract: A method for generating a language model for an organization includes: receiving, by a processor, organization-specific training data; receiving, by the processor, generic training data; computing, by the processor, a plurality of similarities between the generic training data and the organization-specific training data; assigning, by the processor, a plurality of weights to the generic training data in accordance with the computed similarities; combining, by the processor, the generic training data with the organization-specific training data in accordance with the weights to generate customized training data; training, by the processor, a customized language model using the customized training data; and outputting, by the processor, the customized language model, the customized language model being configured to compute the likelihood of phrases in a medium.

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