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公开(公告)号：WO2019118377A1
公开(公告)日：2019-06-20
申请号：PCT/US2018/064810
申请日：2018-12-11
Inventor： MAZZA, Arnon , FAIZAKOF, Avraham , LEV-TOV, Amir , TAPUHI, Tamir , KONIG, Yochai
IPC: G06F17/00
Abstract: A method for configuring a topic-specific chatbot comprising: clustering a plurality of transcripts of interactions between customers and agents of a contact center of an enterprise to generate a plurality of clusters of interactions, each cluster of interactions corresponding to a topic, each of the interactions including agent phrases and customer phrases; for each cluster of the plurality of clusters of interactions: extracting a topic-specific dialogue tree for the cluster; pruning the topic-specific dialogue tree to generate a deterministic dialogue tree; and configuring a topic-specific chatbot in accordance with the deterministic dialogue tree; and outputting the one or more topic-specific chatbots, each of the topic-specific chatbots being configured to generate, automatically, responses to messages regarding the topic of the topic-specific chatbot from a customer in an interaction between the customer and the enterprise.
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2.发明申请SYSTEM AND METHOD FOR INTERACTIVE MULTI-RESOLUTION TOPIC DETECTION AND TRACKING 审中-公开用于交互式多分辨率主题检测和跟踪的系统和方法
公开(公告)号：WO2016109605A1
公开(公告)日：2016-07-07
申请号：PCT/US2015/067963
申请日：2015-12-29
Inventor： LEV, Yoni , FAIZAKOF, Avraham , LEV-TOV, Amir , TAPUHI, Tamir , KONIG, Yochai
CPC classification number: G06F17/30976 , G06F17/30713 , G06Q30/0281 , G06Q50/01
Abstract: A method for tracking known topics in a plurality of interactions includes: extracting, by a processor, a plurality of fragments from the plurality of interactions; initializing, by the processor, a collection of tracked topics to an empty collection; computing, by the processor, a similarity between each fragment of the fragments and each of the known topics; and adding, by the processor, a known topic of the known topics to the tracked topics in response to the similarity between a fragment and the known topic exceeding a threshold value.
Abstract translation: 用于跟踪多个交互中的已知主题的方法包括：由处理器从多个交互中提取多个片段; 由处理器将跟踪主题的集合初始化为空集合; 由处理器计算片段的每个片段和每个已知主题之间的相似度; 以及响应于片段和超过阈值的已知主题之间的相似度，由处理器将已知主题的已知主题添加到所跟踪的主题。
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公开(公告)号：WO2016007792A1
公开(公告)日：2016-01-14
申请号：PCT/US2015/039816
申请日：2015-07-09
Inventor： FAIZAKOF, Avraham , LEV, Yoni , LEV-TOV, Amir , KONIG, Yochai
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。
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公开(公告)号：WO2015013554A1
公开(公告)日：2015-01-29
申请号：PCT/US2014/048089
申请日：2014-07-24
Inventor： LEV-TOV, Amir , FAIZAKOF, Avraham , OLLINGER, David , KONIG, Yochai
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：WO2020106267A1
公开(公告)日：2020-05-28
申请号：PCT/US2018/061782
申请日：2018-11-19
Inventor： LEV-TOV, Amir , FAIZAKOF, Avraham , MAZZA, Arnon , KONIG, Yochai
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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Patent Agency Ranking
公开(公告)号：WO2018064199A2
公开(公告)日：2018-04-05
申请号：PCT/US2017/053779
申请日：2017-09-27
Inventor： LEV-TOV, Amir , TAPUHI, Tamir , FAIZAKOF, Avraham , KONIG, David , KONIG, Yochai
CPC classification number: G06Q30/06 , G06Q10/0639 , G06Q10/06398 , G06Q10/105 , G06Q30/01 , G06Q30/016 , G09B7/07
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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7.发明申请DATA DRIVEN SPEECH ENABLED SELF-HELP SYSTEMS AND METHODS OF OPERATING THEREOF 审中-公开数据驱动语音启用自助系统及其操作方法
公开(公告)号：WO2017011343A1
公开(公告)日：2017-01-19
申请号：PCT/US2016/041626
申请日：2016-07-08
Inventor： LEV, Yoni , TAPUHI, Tamir , FAIZAKOF, Avraham , LEV-TOV, Amir , KONIG, Yochai
CPC classification number: G06F17/2775 , G10L15/1815 , G10L15/1822 , G10L15/19 , G10L2015/223
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.
Abstract translation: 基于多个客户和多个代理之间的先前交互来配置自动语音驱动的自助系统的方法包括：由处理器识别客户和代理之间的先前交互中的语音以产生识别的文本; 由所述处理器检测所识别的文本中的多个短语; 由所述处理器将所述多个短语聚类成多个聚类; 由所述处理器生成描述所述簇中的相应簇的多个语法; 由所述处理器输出所述多个语法; 并且基于多个语法来调用自动化自助系统的配置。
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8.发明申请
公开(公告)号：WO2014105912A1
公开(公告)日：2014-07-03
申请号：PCT/US2013/077712
申请日：2013-12-24
Applicant: GENESYS TELECOMMUNICATIONS LABORATORIES INC.
Inventor： LEV-TOV, Amir , FAIZAKOF, Avraham , KONIG, Yochai
CPC classification number: G10L15/19 , G06F17/30389 , G06F17/30746 , G06F17/30769 , G10L15/02 , G10L15/08 , G10L15/1815 , G10L15/30
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.
Abstract translation: 一种方法，包括：在计算机系统上接收文本搜索查询，所述查询包括一个或多个查询词; 在所述计算机系统上为所述查询中的每个查询词生成多个语音识别处理的音频文件内的一个或多个锚段，所述一个或多个锚段标识包含所述查询词的可能位置; 在所述计算机系统上对所述一个或多个锚段进行后处理，所述后处理包括：扩展所述一个或多个锚段; 对一个或多个锚段进行排序; 并且合并所述一个或多个锚段中的重叠部分; 以及在所述计算机系统上使用约束语法来搜索所述后处理的一个或多个锚段，以针对所述一个或多个查询词中的至少一个的实例。
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9.发明申请PREDICTING RECOGNITION QUALITY OF A PHRASE IN AUTOMATIC SPEECH RECOGNITION SYSTEMS 审中-公开在自动语音识别系统中预测认知质量
公开(公告)号：WO2015066386A1
公开(公告)日：2015-05-07
申请号：PCT/US2014/063265
申请日：2014-10-30
Inventor： LEV-TOV, Amir , FAIZAKOF, Avraham , KONIG, Yochai
IPC: G10L15/01 , G10L15/02 , G10L15/183
Abstract: A method for predicting a speech recognition quality of a phrase comprising at least one word includes: receiving, on a computer system including a processor and memory storing instructions, the phrase; computing, on the computer system, a set of features comprising one or more features corresponding to the phrase; providing the phrase to a prediction model on the computer system and receiving a predicted recognition quality value based on the set of features; and returning the predicted recognition quality value.
Abstract translation: 用于预测包括至少一个单词的短语的语音识别质量的方法包括：在包括处理器的计算机系统和存储指令的存储器上接收短语; 在所述计算机系统上计算包括与所述短语相对应的一个或多个特征的一组特征; 将所述短语提供给所述计算机系统上的预测模型，并且基于所述特征集合接收预测的识别质量值; 并返回预测的识别质量值。
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公开(公告)号：WO2022146861A1
公开(公告)日：2022-07-07
申请号：PCT/US2021/065040
申请日：2021-12-23
Inventor： FAIZAKOF, Avraham , MAZZA, Arnon , HAIKIN, Lev , ORBACH, Eyal
IPC: G06F40/232 , G06F40/284 , G06N20/00 , G10L15/00
Abstract: A method comprising: receiving a first text corpus comprising punctuated and capitalized text; annotating words in said first text corpus with a set of labels indicating a punctuation and a capitalization of each word; at an initial training stage, training a machine learning model on a first training set comprising: (i) said annotated words in said first text corpus, and (ii) said labels; receiving a second text corpus representing conversational speech; annotating words in said second text corpus with said set of labels; at a re-training stage, re-training said machine learning model on a second training set comprising: (iii) said annotated words in said second text corpus, and (iv) said labels; and at an inference stage, applying said trained machine learning model to a target set of words representing conversational speech, to predict a punctuation and capitalization of each word in said target set.
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