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公开(公告)号：US10789430B2
公开(公告)日：2020-09-29
申请号：US16194758
申请日：2018-11-19
Inventor： Amir Lev Tov , Avraham Faizakof , Arnon Mazza , Yochai Konig
IPC: G06F40/00 , 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：US20200059558A1
公开(公告)日：2020-02-20
申请号：US16664904
申请日：2019-10-27
Inventor： Arnon Mazza , Avraham Faizakof , Amir Lev-Tov , Tamir Tapuhi , Yochai Konig
Abstract: A system and method are presented for configuring topic-specific chatbots. Clustering interaction transcripts between customers and agents of a contact center is performed to generated a plurality of interaction clusters. The clusters corresponding a topic. Topic-specific dialogue trees are extracted for each cluster. The trees comprise nodes connected by edges. The topic-specific dialogue tree is modified to generate a deterministic dialogue tree. The deterministic dialogue tree is used to configure a topic-specific chatbot to generate and automatically respond to messages regarding the topic.
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公开(公告)号：US20200007682A1
公开(公告)日：2020-01-02
申请号：US16567513
申请日：2019-09-11
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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公开(公告)号：US10515150B2
公开(公告)日：2019-12-24
申请号：US14799369
申请日：2015-07-14
Inventor： Yoni Lev , Tamir Tapuhi , Avraham Faizakof , Amir Lev-Tov , Yochai Konig
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.
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公开(公告)号：US10319366B2
公开(公告)日：2019-06-11
申请号：US15478108
申请日：2017-04-03
Inventor： Amir Lev-Tov , Avraham Faizakof , Yochai Konig
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.
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Patent Agency Ranking
公开(公告)号：US10290301B2
公开(公告)日：2019-05-14
申请号：US15402070
申请日：2017-01-09
Inventor： Amir Lev-Tov , Avraham Faizakof , Yochai Konig
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.
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公开(公告)号：US10061867B2
公开(公告)日：2018-08-28
申请号：US14586730
申请日：2014-12-30
Inventor： Yoni Lev , Avraham Faizakof , Amir Lev-Tov , Tamir Tapuhi , Yochai Konig
CPC classification number: G06F16/90332 , G06F16/358 , 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.
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公开(公告)号：US20160012818A1
公开(公告)日：2016-01-14
申请号：US14327476
申请日：2014-07-09
Inventor： Avraham Faizakof , Yoni Lev , Amir Lev-Tov , Yochai Konig
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：US11586828B2
公开(公告)日：2023-02-21
申请号：US17002352
申请日：2020-08-25
Inventor： Amir Lev-Tov , Avraham Faizakof , Arnon Mazza , Yochai Konig
IPC: G06F40/30 , 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：US11341986B2
公开(公告)日：2022-05-24
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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