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    Data-driven dialogue enabled self-help systems
    12.
    发明授权
    Data-driven dialogue enabled self-help systems 有权

    公开(公告)号：US10382623B2

    公开(公告)日：2019-08-13

    申请号：US14919673

    申请日：2015-10-21

    Applicant: GENESYS TELECOMMUNICATIONS LABORATORIES, INC.

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

    IPC: G06F17/27 ,  H04M3/493

    Abstract: A method for configuring an automated self-help system based on prior interactions between a plurality of customers and a plurality of agents of a contact center includes: recognizing, by a processor, speech in the prior interactions between customers and agents to generate recognized text, the recognized text including a plurality of phrases, the phrases being classified into a plurality of clusters; extracting, by the processor, a plurality of sequences of clusters, each of the sequences of clusters corresponding to the phrases of one of the prior interactions; filtering, by the processor, the sequences of clusters based on a criterion; mining, by the processor, a preliminary dialog tree from the sequences of clusters; invoking configuration of the automated self-help system based on the preliminary dialog tree; and outputting a dialog tree for configuring the automated self-help system.

    LANGUAGE MODEL CUSTOMIZATION IN SPEECH RECOGNITION FOR SPEECH ANALYTICS
    13.
    发明申请
    LANGUAGE MODEL CUSTOMIZATION IN SPEECH RECOGNITION FOR SPEECH ANALYTICS 审中-公开

    公开(公告)号：US20190122653A1

    公开(公告)日：2019-04-25

    申请号：US16219537

    申请日：2018-12-13

    Applicant: Genesys Telecommunications Laboratories, Inc.

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

    IPC: G10L15/06 ,  G06N20/00 ,  G06F17/27 ,  G10L15/26

    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.

    GENERALIZED PHRASES IN AUTOMATIC SPEECH RECOGNITION SYSTEMS
    15.
    发明申请
    GENERALIZED PHRASES IN AUTOMATIC SPEECH RECOGNITION SYSTEMS 有权
    自动语音识别系统中的通用语法

    公开(公告)号：US20150194149A1

    公开(公告)日：2015-07-09

    申请号：US14150628

    申请日：2014-01-08

    Applicant: GENESYS TELECOMMUNICATIONS LABORATORIES, INC.

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

    IPC: G10L15/18 ,  G10L15/19

    CPC classification number: G06F17/2785 ,  G10L15/063 ,  G10L15/1815 ,  G10L15/1822 ,  G10L15/19 ,  G10L15/193

    Abstract: A method for generating a suggested phrase having a similar meaning to a supplied phrase in an analytics system includes: receiving, on a computer system comprising a processor and memory storing instructions, the supplied phrase, the supplied phrase including one or more terms; identifying, on the computer system, a term of the phrase belonging to a semantic group; generating the suggested phrase using the supplied phrase and the semantic group; and returning the suggested phrase.

    Abstract translation: 一种用于生成与分析系统中提供的短语具有相似含义的建议短语的方法，包括：在包括处理器的计算机系统和存储指令的存储器上接收所提供的短语，所提供的短语包括一个或多个术语; 在计算机系统上识别属于语义组的短语的术语; 使用提供的短语和语义组生成建议短语; 并返回建议的短语。

    SYSTEM AND METHOD FOR DISCOVERING AND EXPLORING CONCEPTS
    16.
    发明申请
    SYSTEM AND METHOD FOR DISCOVERING AND EXPLORING CONCEPTS 有权
    用于发现和探索概念的系统和方法

    公开(公告)号：US20150032452A1

    公开(公告)日：2015-01-29

    申请号：US13952459

    申请日：2013-07-26

    Applicant: GENESYS TELECOMMUNICATIONS LABORATORIES, INC.

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

    IPC: G10L15/18

    CPC classification number: G06F17/2785 ,  G06F17/3071 ,  G10L15/1822

    Abstract: A method for identifying concepts in a plurality of interactions includes: filtering, on a processor, the interactions based on intervals; creating, on the processor, a plurality of sentences from the filtered interactions; computing, on the processor, a saliency of each the sentences; pruning away, on the processor, sentences with low saliency for generating a set of informative sentences; clustering, on the processor, the sentences of the set of informative sentences for generating a plurality of sentence clusters, each of the clusters corresponding to a concept of the concepts; computing, on the processor, a saliency of each of the clusters; and naming, on the processor, each of the clusters.

    Abstract translation: 用于识别多个交互中的概念的方法包括：在处理器上基于间隔过滤所述交互; 在所述处理器上从所述过滤的相互作用中创建多个句子; 在处理器上计算每个句子的显着性; 在处理器上修剪，低显着的句子产生一组信息句子; 在处理器上聚集用于生成多个句子簇的信息语句集合的句子，每个集群对应于概念的概念; 在处理器上计算每个集群的显着性; 并在处理器上命名每个集群。

    DIALOGUE FLOW OPTIMIZATION AND PERSONALIZATION
    20.
    发明申请
    DIALOGUE FLOW OPTIMIZATION AND PERSONALIZATION 审中-公开

    公开(公告)号：US20200007682A1

    公开(公告)日：2020-01-02

    申请号：US16567513

    申请日：2019-09-11

    Applicant: Genesys Telecommunications Laboratories, Inc.

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

    IPC: H04M3/493

    Abstract: A method for generating a dialogue 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 dialogue tree in accordance with the rated feature vectors for configuring the automated self-help system.

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