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公开(公告)号：US10824814B2
公开(公告)日：2020-11-03
申请号：US15811311
申请日：2017-11-13
Inventor： Avraham Faizakof , Amir Lev-Tov , David Ollinger , Yochai Konig
IPC: G06F40/30 , G10L15/18 , G10L15/19 , G10L15/06 , 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.
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公开(公告)号：US10382623B2
公开(公告)日：2019-08-13
申请号：US14919673
申请日：2015-10-21
Inventor： Amir Lev-Tov , Tamir Tapuhi , Yoni Lev , Avraham Faizakof , Yochai Konig
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.
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公开(公告)号：US20190122653A1
公开(公告)日：2019-04-25
申请号：US16219537
申请日：2018-12-13
Inventor： Tamir Tapuhi , Amir Lev-Tov , Avraham Faizakof , Yochai Konig
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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公开(公告)号：US20180096278A1
公开(公告)日：2018-04-05
申请号：US15282897
申请日：2016-09-30
Inventor： Amir Lev-Tov , Tamir Tapuhi , Avraham Faizakof , David Konig , Yochai Konig
CPC classification number: G06Q10/06395 , G06F16/9535 , G06Q10/1095 , G10L15/22 , G10L2015/228
Abstract: A method includes: receiving, by a processor, an evaluation form including a plurality of evaluation questions; receiving, by the processor, an interaction to be evaluated by the evaluation form; selecting, by the processor, an evaluation question of the evaluation form, the evaluation question including a rule associated with one or more topics, each of the topics including one or more words or phrases; searching, by the processor, the interaction for the one or more topics of the rule in accordance with the presence of one or more words or phrases in the interaction to generate a search result; calculating, by the processor, an answer to the evaluation question in accordance with the rule and the search result; and outputting, by the processor, the calculated answer to the evaluation question of the evaluation form.
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公开(公告)号：US20150194149A1
公开(公告)日：2015-07-09
申请号：US14150628
申请日：2014-01-08
Inventor： Avraham Faizakof , Amir Lev-Tov , David Ollinger , Yochai Konig
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。
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Patent Agency Ranking
公开(公告)号：US20150032452A1
公开(公告)日：2015-01-29
申请号：US13952459
申请日：2013-07-26
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。
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公开(公告)号：US11562148B2
公开(公告)日：2023-01-24
申请号：US17002282
申请日：2020-08-25
Inventor： Amir Lev-Tov , Avraham Faizakof , Arnon Mazza , Yochai Konig
IPC: G06F40/20 , G06F40/35 , G06K9/62 , G06F40/284
Abstract: Methods, systems, and computer program product for automatically performing sentiment analysis on texts, such as telephone call transcripts and electronic written communications. Disclosed techniques include, inter alia, lexicon training, handling of negations and shifters, pruning of lexicons, confidence calculation for token orientation, supervised customization, lexicon mixing, and adaptive segmentation.
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公开(公告)号：US20210193169A1
公开(公告)日：2021-06-24
申请号：US16723154
申请日：2019-12-20
Inventor： Avraham Faizakof , Lev Haikin , Yochai Konig , Arnon Mazza
Abstract: A method comprising: receiving a plurality of audio segments comprising a speech signal, wherein said audio segments represent a plurality of verbal interactions; receiving labels associated with an emotional state expressed in each of said audio segments; dividing each of said audio segments into a plurality of frames, based on a specified frame duration; extracting a plurality of acoustic features from each of said frames; computing statistics over said acoustic features with respect to sequences of frames representing phoneme boundaries in said audio segments; at a training stage, training a machine learning model on a training set comprising: said statistics associated with said audio segments, and said labels; and at an inference stage, applying said trained model to one or more target audio segments comprising a speech signal, to detect an emotional state expressed in said target audio segments.
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公开(公告)号：US10455088B2
公开(公告)日：2019-10-22
申请号：US14919675
申请日：2015-10-21
Inventor： Tamir Tapuhi , Yochai Konig , Amir Lev-Tov , Avraham Faizakof , Yoni Lev
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.
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公开(公告)号：US10186255B2
公开(公告)日：2019-01-22
申请号：US15247645
申请日：2016-08-25
Inventor： Tamir Tapuhi , Amir Lev-Tov , Avraham Faizakof , Yochai Konig
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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