Patents by Inventor Arnon Mazza
Arnon Mazza has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240087187Abstract: Systems and method for visualizing data for an automated question answering system are disclosed. The method includes identifying a first answer associated with a first query; identifying a second answer associated with a second query; determining a criterion of the first answer with respect to the second answer; and visually representing the first answer and the second answer based on the criterion.Type: ApplicationFiled: September 12, 2022Publication date: March 14, 2024Inventors: Charles Wooters, Yochai Konig, Christos Melidis, Arnon Mazza, George Seif, Chen Qian, Ives José de Albuquerque Macêdo, JR., Jérôme Solis
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Patent number: 11676044Abstract: Systems and methods for generating a chatbot are disclosed. Source data is identified. A first chunk of the source data is also identified. A first machine learning model is executed for automatically generating a first candidate question associated with the first chunk. A determination is made as to whether the first candidate question satisfies a criterion. The first candidate question is output as training data for training the chatbot in response to the determination.Type: GrantFiled: August 16, 2022Date of Patent: June 13, 2023Assignee: ADA SUPPORT INC.Inventors: Arnon Mazza, Christos Melidis
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Publication number: 20230144379Abstract: A system and method of automatically discovering unigrams in a speech data element may include receiving a language model that includes a plurality of n-grams, where each n-gram includes one or more unigrams; applying an acoustic machine-learning (ML) model on one or more speech data elements to obtain a character distribution function; applying a greedy decoder on the character distribution function, to predict an initial corpus of unigrams; filtering out one or more unigrams of the initial corpus to obtain a corpus of candidate unigrams, where the candidate unigrams are not included in the language model; analyzing the one or more first speech data elements, to extract at least one n-gram that comprises a candidate unigram; and updating the language model to include the extracted at least one n-gram.Type: ApplicationFiled: November 8, 2021Publication date: May 11, 2023Applicant: GENESYS CLOUD SERVICES, INC.Inventors: LEV HAIKIN, ARNON MAZZA, EYAL ORBACH, AVRAHAM FAIZAKOF
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Patent number: 11645460Abstract: A first text corpus comprising punctuated and capitalized text is received. The words in the first text corpus are then annotated with a set of labels indicating a punctuation and a capitalization of each word. At an initial training stage, a machine learning model is trained on a first training set using the annotated words from the first text corpus and the labels. A second text corpus is received representing conversational speech. The words in the second text corpus are then annotated with the set of labels. In a re-training stage, the machine learning model is re-trained on a second training set comprising the annotated words from the second text corpus, and the labels. At an inference stage, the trained machine learning model is applied to a target set of words representing conversational speech to predict a punctuation and capitalization of each word in the target set.Type: GrantFiled: December 28, 2020Date of Patent: May 9, 2023Inventors: Avraham Faizakof, Arnon Mazza, Lev Haikin, Eyal Orbach
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Patent number: 11586828Abstract: 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.Type: GrantFiled: August 25, 2020Date of Patent: February 21, 2023Inventors: Amir Lev-Tov, Avraham Faizakof, Arnon Mazza, Yochai Konig
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Patent number: 11562148Abstract: 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.Type: GrantFiled: August 25, 2020Date of Patent: January 24, 2023Inventors: Amir Lev-Tov, Avraham Faizakof, Arnon Mazza, Yochai Konig
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Patent number: 11551011Abstract: 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.Type: GrantFiled: August 25, 2020Date of Patent: January 10, 2023Inventors: Amir Lev-Tov, Avraham Faizakof, Arnon Mazza, Yochai Konig
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Publication number: 20220382982Abstract: A method and system for automatic topic detection in text may include receiving a text document of a corpus of documents and extracting one or more phrases from the document, based on one or more syntactic patterns. For each phrase, embodiments of the invention may: apply a word embedding neural network on one or more words of the phrase, to obtain one or more respective word embedding vectors; calculate a weighted phrase embedding vector, and compute a phrase saliency score, based on the weighted phrase embedding vector. Embodiments of the invention may subsequently produce one or more topic labels, representing one or more respective topics in the document, based on the computed phrase saliency scores, and may select one or more topic labels according to their relevance to the business domain of the corpus.Type: ApplicationFiled: May 12, 2021Publication date: December 1, 2022Applicant: GENESYS CLOUD SERVICES, INC.Inventors: EYAL ORBACH, AVRAHAM FAIZAKOF, ARNON MAZZA, LEV HAIKIN
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Publication number: 20220366197Abstract: A method and system for finetuning automated sentiment classification by at least one processor may include: receiving a first machine learning (ML) model M0, pretrained to perform automated sentiment classification of utterances, based on a first annotated training dataset; associating one or more instances of model M0 to one or more corresponding sites; and for one or more (e.g., each) ML model M0 instance and/or site: receiving at least one utterance via the corresponding site; obtaining at least one data element of annotated feedback, corresponding to the at least one utterance; retraining the ML model M0, to produce a second ML model Mi, based on a second annotated training dataset, wherein the second annotated training dataset may include the first annotated training dataset and the at least one annotated feedback data element; and using the second ML model Mi, to classify utterances according to one or more sentiment classes.Type: ApplicationFiled: May 12, 2021Publication date: November 17, 2022Applicant: GENESYS CLOUD SERVICES, INC.Inventors: ARNON MAZZA, LEV HAIKIN, EYAL ORBACH, AVRAHAM FAIZAKOF
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Patent number: 11425254Abstract: 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.Type: GrantFiled: October 27, 2019Date of Patent: August 23, 2022Inventors: Arnon Mazza, Avraham Faizakof, Amir Lev-Tov, Tamir Tapuhi, Yochai Konig
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Patent number: 11425255Abstract: A system and method are presented for dialogue tree generation. The dialogue tree may be used for generating a chatbot. Similar phrases from phrases comprising the interactions between a first party and a second party are group together from the first party of a cluster. For each group of similar phrases, percentages are determined and compared against a threshold occurrence rate. Anchors are generated and used in alignment in the determination of dialogue flows. Topic-specific dialogue trees may be determined from the dialogue flows. The topic-specific dialogue trees may be modified to generate a deterministic dialogue tree.Type: GrantFiled: October 27, 2019Date of Patent: August 23, 2022Inventors: Arnon Mazza, Avraham Faizakof, Amir Lev-Tov, Tamir Tapuhi, Yochai Konig
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Publication number: 20220208176Abstract: 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.Type: ApplicationFiled: December 28, 2020Publication date: June 30, 2022Applicant: GENESYS TELECOMMUNICATIONS LABORATORIES, INC.Inventors: AVRAHAM FAIZAKOF, ARNON MAZZA, LEV HAIKIN, EYAL ORBACH
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Patent number: 11341986Abstract: 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.Type: GrantFiled: December 20, 2019Date of Patent: May 24, 2022Inventors: Avraham Faizakof, Lev Haikin, Yochai Konig, Arnon Mazza
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Patent number: 11170168Abstract: A method, system, and computer program product for unsupervised automated generation of lexicons in a specified target domain, comprising tokens having domain-specific sentiment orientation, by selecting a seed set of tokens from a source lexicon; generating a candidate set of tokens from a text corpus in the target domain based on a similarity parameter with the seed set; calculating a sentiment score for each of the tokens in the candidate set; and automatically updating the source lexicon based on the candidate list.Type: GrantFiled: April 11, 2019Date of Patent: November 9, 2021Inventors: Amir Lev-Tov, Avraham Faizakof, Arnon Mazza, Yochai Konig
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Publication number: 20210193169Abstract: 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.Type: ApplicationFiled: December 20, 2019Publication date: June 24, 2021Inventors: Avraham Faizakof, Lev Haikin, Yochai Konig, Arnon Mazza
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Publication number: 20200410172Abstract: 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.Type: ApplicationFiled: August 25, 2020Publication date: December 31, 2020Applicant: GENESYS TELECOMMUNICATIONS LABORATORIES, INC.Inventors: AMIR LEV-TOV, AVRAHAM FAIZAKOF, ARNON MAZZA, YOCHAI KONIG
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Publication number: 20200410171Abstract: 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.Type: ApplicationFiled: August 25, 2020Publication date: December 31, 2020Applicant: GENESYS TELECOMMUNICATIONS LABORATORIES, INC.Inventors: AMIR LEV-TOV, AVRAHAM FAIZAKOF, ARNON MAZZA, YOCHAI KONIG
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Publication number: 20200387674Abstract: 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.Type: ApplicationFiled: August 25, 2020Publication date: December 10, 2020Applicant: GENESYS TELECOMMUNICATIONS LABORATORIES, INC.Inventors: Amir LEV-TOV, AVRAHAM FAIZAKOF, ARNON MAZZA, YOCHAI KONIG
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Publication number: 20200327191Abstract: A method, system, and computer program product for unsupervised automated generation of lexicons in a specified target domain, comprising tokens having domain-specific sentiment orientation, by selecting a seed set of tokens from a source lexicon; generating a candidate set of tokens from a text corpus in the target domain based on a similarity parameter with the seed set; calculating a sentiment score for each of the tokens in the candidate set; and automatically updating the source lexicon based on the candidate list.Type: ApplicationFiled: April 11, 2019Publication date: October 15, 2020Inventors: Amir Lev-Tov, Avraham Faizakof, Arnon Mazza, Yochai Konig
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Patent number: 10789430Abstract: 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.Type: GrantFiled: November 19, 2018Date of Patent: September 29, 2020Inventors: Amir Lev Tov, Avraham Faizakof, Arnon Mazza, Yochai Konig