Patents by Inventor Hila WEISMAN
Hila WEISMAN 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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Patent number: 11005995Abstract: A system and method for generating an agent behavioral analytics including transcribing an incoming call to produce a call transcription; and using a trained convolutional neural network (CNN) to produce behavioral labels for the agent in the incoming call for behavioral metrics, based on the call transcription. The CNN may include an embedding layer to convert words in the call transcription into vectors in a word embedding space; a convolution layer to perform a plurality of convolutions on the vectors and to generate vectors of features; a pooling layer to concatenate the vectors of features to a single vector by taking a maximum of each feature generated by the convolution layer; and a classification layer to produce grades of the agent in the incoming call for the set of attributes or behavioral metrics, based on the single vector generated by the pooling layer.Type: GrantFiled: February 10, 2019Date of Patent: May 11, 2021Assignee: NICE LTD.Inventors: Hila Weisman, Raanan Gonen, Rana Daoud, Hila Kneller
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Patent number: 10839335Abstract: A system and method for generating an agent behavioral analytics including extracting text-based features, sentiment-based features, and prosody-based features from tagged calls; training a machine learning behavioral model, based on the text-based features, the sentiment-based features, and the prosody-based features extracted from the tagged calls and an at least one score associated with an at least one behavioral metric of the tagged calls, to produce a trained machine learning behavioral model; extracting text-based features, sentiment-based features, and prosody-based features from an incoming call; and using the trained machine learning behavioral model to produce an at least one behavioral label for the agent in the incoming call for the at least one behavioral metric, based on the text-based features of the incoming call, the sentiment-based features of the incoming call and the prosody-based features of the incoming call.Type: GrantFiled: December 13, 2018Date of Patent: November 17, 2020Assignee: NICE LTD.Inventors: Hila Weisman, Raanan Gonen, Rana Daoud
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Patent number: 10803241Abstract: Systems and methods for text normalization in a plurality of noisy channels receive a text entry and channel origin data of the text entry; determine whether the text entry matches an in-vocabulary (IV) entry or whether the text entry is an out-of-vocabulary (OOV) entry; if the text entry is determined to have a matching IV entry, output the matching IV entry, and if the text entry is determined to be an OOV entry, implement a channel-specific error-type adapter framework based on the channel origin data, wherein the channel-specific error-type adapter framework is optimized for a specific channel from which the text entry originated; normalize the text entry using the channel-specific error-type adapter framework; and output one or more candidate normalized forms of the text entry.Type: GrantFiled: December 28, 2015Date of Patent: October 13, 2020Assignee: NICE LTD.Inventors: Hila Weisman, Peter Izsak, Inna Achlow, Victor Shafran
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Publication number: 20200195779Abstract: A system and method for generating an agent behavioral analytics including transcribing an incoming call to produce a call transcription; and using a trained convolutional neural network (CNN) to produce behavioral labels for the agent in the incoming call for behavioral metrics, based on the call transcription. The CNN may include an embedding layer to convert words in the call transcription into vectors in a word embedding space; a convolution layer to perform a plurality of convolutions on the vectors and to generate vectors of features; a pooling layer to concatenate the vectors of features to a single vector by taking a maximum of each feature generated by the convolution layer; and a classification layer to produce grades of the agent in the incoming call for the set of attributes or behavioral metrics, based on the single vector generated by the pooling layer.Type: ApplicationFiled: February 10, 2019Publication date: June 18, 2020Applicant: Nice Ltd.Inventors: Hila Weisman, Raanan Gonen, Rana Daoud, Hila Kneller
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Publication number: 20200193353Abstract: A system and method for generating an agent behavioral analytics including extracting text-based features, sentiment-based features, and prosody-based features from tagged calls; training a machine learning behavioral model, based on the text-based features, the sentiment-based features, and the prosody-based features extracted from the tagged calls and an at least one score associated with an at least one behavioral metric of the tagged calls, to produce a trained machine learning behavioral model; extracting text-based features, sentiment-based features, and prosody-based features from an incoming call; and using the trained machine learning behavioral model to produce an at least one behavioral label for the agent in the incoming call for the at least one behavioral metric, based on the text-based features of the incoming call, the sentiment-based features of the incoming call and the prosody-based features of the incoming call.Type: ApplicationFiled: December 13, 2018Publication date: June 18, 2020Applicant: Nice Ltd.Inventors: Hila WEISMAN, Raanan GONEN, Rana DAOUD
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Patent number: 9953048Abstract: A method for determining prominent keyphrases in interactions, comprising, receiving keyphrases of numerous interactions received via a plurality of channels that comprise apparatuses for conveying the interactions according to the media thereof, quantitatively evaluating each keyphrase by a plurality of different metrics thereby yielding a corresponding plurality of values, and linearly combining the plurality of the values with a corresponding plurality of coefficients associated with a channel via which an interaction having said keyphrase is received, thereby providing a score of said keyphrase, and based on a condition related to the scores of the keyphrases, selecting at least one keyphrase as an at least one prominent keyphrase, wherein the method is at least partially performed by an at least one computerized apparatus configured for interfacing with the apparatuses of the plurality of the channels.Type: GrantFiled: March 5, 2015Date of Patent: April 24, 2018Assignee: NICE LTD.Inventors: Hila Weisman, Peter Izsak, Victor Shafran
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Publication number: 20160335244Abstract: Systems and methods for text normalization in a plurality of noisy channels receive a text entry and channel origin data of the text entry; determine whether the text entry matches an in-vocabulary (IV) entry or whether the text entry is an out-of-vocabulary (OOV) entry; if the text entry is determined to have a matching IV entry, output the matching IV entry, and if the text entry is determined to be an OOV entry, implement a channel-specific error-type adapter framework based on the channel origin data, wherein the channel-specific error-type adapter framework is optimized for a specific channel from which the text entry originated; normalize the text entry using the channel-specific error-type adapter framework; and output one or more candidate normalized forms of the text entry.Type: ApplicationFiled: December 28, 2015Publication date: November 17, 2016Applicant: NICE-SYSTEMS LTD.Inventors: Hila WEISMAN, Peter IZSAK, Inna ACHLOW, Victor SHAFRAN
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Publication number: 20160048546Abstract: A method for determining prominent keyphrases in interactions, comprising, receiving keyphrases of numerous interactions received via a plurality of channels that comprise apparatuses for conveying the interactions according to the media thereof, quantitatively evaluating each keyphrase by a plurality of different metrics thereby yielding a corresponding plurality of values, and linearly combining the plurality of the values with a corresponding plurality of coefficients associated with a channel via which an interaction having said keyphrase is received, thereby providing a score of said keyphrase, and based on a condition related to the scores of the keyphrases, selecting at least one keyphrase as an at least one prominent keyphrase, wherein the method is at least partially performed by an at least one computerized apparatus configured for interfacing with the apparatuses of the plurality of the channels.Type: ApplicationFiled: March 5, 2015Publication date: February 18, 2016Inventors: Hila WEISMAN, Peter Izsak, Victor Shafran