公开(公告)号：WO2023081504A1

公开(公告)日：2023-05-11

申请号：PCT/US2022/049251

申请日：2022-11-08

Applicant: GENESYS CLOUD SERVICES, INC.

Inventor： HAIKIN, Lev ,  MAZZA, Arnon ,  ORBACH, Eyal ,  FAIZAKOF, Avraham

IPC: G10L15/197 ,  G10L15/06

Abstract: 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.

公开(公告)号：WO2023049158A1

公开(公告)日：2023-03-30

申请号：PCT/US2022/044214

申请日：2022-09-21

Applicant: GENESYS CLOUD SERVICES, INC.

Inventor： KASSEL, Robert

IPC: G06Q10/06

Abstract: A method for routing incoming interactions in a contact center. The incoming interactions are instigated by customers for communicating with the contact center, and the contact center includes agents between which the incoming interactions are routed. The method includes: determining a routing interval; identifying received incoming interactions for inclusion in a received interactions batch, each of the received incoming interactions being identified as ones of the incoming interactions that are received within the routing interval; identifying candidate agents for inclusion in a candidate agent group, the candidate agents being identified as available ones of the agents to whom the received incoming interactions of the received interaction batch can be routed; and subsequent to the end of the routing interval, routing the received incoming interactions included in the received interaction batch to the candidate agents included in the candidate agent group.

公开(公告)号：WO2022265990A1

公开(公告)日：2022-12-22

申请号：PCT/US2022/033248

申请日：2022-06-13

Applicant: GENESYS CLOUD SERVICES, INC.

Inventor： WYSS, Felix, Immanuel ,  JAHNS, Matthew

IPC: H04L51/02 ,  H04L65/1083 ,  H04L65/40 ,  H04L65/80

Abstract: A method of dynamic prioritization of collaboration between human and virtual agents according to an embodiment includes generating a priority score for a conversation between a human user and a chat bot, wherein the priority score is based on at least a sentiment of the human user and a temporal aspect of the conversation, providing the priority score to a human agent via an interface for monitoring the priority score, transferring control of the conversation from the chat bot to the human agent based on an interaction of the human agent with the interface, and yielding control of the conversation from the human agent back to the chat bot in response to another interaction of the human agent with the interface.

公开(公告)号：WO2022133179A1

公开(公告)日：2022-06-23

申请号：PCT/US2021/063970

申请日：2021-12-17

Applicant: GENESYS CLOUD SERVICES, INC.

Inventor： MAZOR, Igal ,  ISMAH-MOSHE, Yaron

IPC: G06F40/30 ,  G06N3/08 ,  G06N3/04 ,  G06F40/284

Abstract: A method for training a multi-class classification model includes receiving training data corresponding to a plurality of classes. For each class in the plurality of classes, the method includes training a binary classification model configured to determine whether or not an observation of training data belongs to the class and for each observation of training data identified as belonging to the class, extracting one or more class identification features from the observation of training data based on activations of an intermediate attention layer in the binary classification model. A multi-class classification model is trained using the class identification features extracted for each of the plurality of classes.

公开(公告)号：WO2022051538A1

公开(公告)日：2022-03-10

申请号：PCT/US2021/048918

申请日：2021-09-02

Applicant: GENESYS CLOUD SERVICES, INC.

Inventor： ASOKAN, Anantha Krishnan ,  GOKULAKANNAN, Balaji ,  JAYARAGHAVENDRAN, Vidhyasimham

IPC: G06Q10/06

Abstract: A method related to predicting agent attrition rate that includes: providing an attrition model; measuring and recording agent journey data of a first agent of a contact center, the agent journey data describing aspects related to an employment of the first agent and having data types that corresponds in kind to data types of inputs of the attrition model; determining that prediction of an attrition rate of the first agent is required; using the attrition model to predict the attrition rate by providing values for the inputs from applicable values taken from the agent journey data of the first agent, and calculating the attrition rate as the output of the attrition model; determining if the calculated current attrition rate indicates a high risk of attrition; and transmitting an alert communication to a supervisor of the first agent.

公开(公告)号：WO2023287778A1

公开(公告)日：2023-01-19

申请号：PCT/US2022/036808

申请日：2022-07-12

Applicant: GENESYS CLOUD SERVICES, INC.

Inventor： MAZOR, Igal ,  ISMAH-MOSHE, Yaron

IPC: G06F16/35 ,  G06F16/33

Abstract: A computer implemented method of document classification includes receiving a text document. A first classification is generated for the document, and a text corpus is searched for one or more terms from the document. Searched terms having an incidence in the text corpus lower than a threshold incidence are flagged, and at least one classification is generated after removing at least one flagged term from the document. An output is generated if the further classification is different from the first classification.

公开(公告)号：WO2022241018A1

公开(公告)日：2022-11-17

申请号：PCT/US2022/028811

申请日：2022-05-11

Applicant: GENESYS CLOUD SERVICES, INC.

Inventor： STOOPS, Daniel, Stewart ,  BELL, Cliff, W.

IPC: G06F16/9535 ,  G06F40/30 ,  G06N5/02 ,  G06N5/04 ,  H04L51/02 ,  G06F16/2458 ,  G06N3/08 ,  G06N20/00 ,  G06F16/9538 ,  G06F40/226 ,  G06F40/211 ,  G06F40/40 ,  G06N5/022 ,  G06Q30/016

Abstract: A method of training an artificial intelligence system to handle long-tail interactions according to an embodiment includes receiving a user question from a user, analyzing the user question with a natural language understanding engine to determine whether an intent of the user question matches an answer in an answer knowledgebase of the system, transferring at least the user question of the interaction to a primary subject matter expert in response to determining that the intent of the user question does not match an answer in the answer knowledgebase, receiving an expert answer to the user question from the primary subject matter expert, transferring an interaction package including the user question and the expert answer to at least one evaluator for validation, and automatically training the natural language understanding engine based on the user question and the expert answer in response to successful validation of the expert answer.

公开(公告)号：WO2022240405A1

公开(公告)日：2022-11-17

申请号：PCT/US2021/032007

申请日：2021-05-12

Applicant: GENESYS CLOUD SERVICES, INC.

Inventor： ORBACH, Eyal ,  FAIZAKOF, Avraham ,  MAZZA, Arnon ,  HAIKIN, Lev

IPC: G06F40/258

Abstract: 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.

公开(公告)号：WO2022240404A1

公开(公告)日：2022-11-17

申请号：PCT/US2021/031991

申请日：2021-05-12

Applicant: GENESYS CLOUD SERVICES, INC.

Inventor： MAZZA, Arnon ,  HAIKIN, Lev ,  ORBACH, Eyal ,  FAIZAKOF, Avraham

IPC: G06F40/30 ,  G06F18/2113 ,  G06F18/217 ,  G06F18/241 ,  G06F18/2431 ,  G06F18/40 ,  G06N20/20

Abstract: 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 M1, 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 M1, to classify utterances according to one or more sentiment classes.

公开(公告)号：WO2023023274A1

公开(公告)日：2023-02-23

申请号：PCT/US2022/040795

申请日：2022-08-18

Applicant: GENESYS CLOUD SERVICES, INC.

Inventor： GRAF, Peter ,  XIAO, James ,  BATES, Anthony ,  LINZY, Christina ,  MAYER, Nathan

IPC: G06Q10/06

Abstract: A method for measuring experience quality. The method including: receiving key experience aspects ("KEAs"); administering pre-surveys to a representative subset of the experience audience, including an importance pre-survey requesting relative importance between the KEAs; and perception pre-survey requesting how closely perceptions align with each KEAs; calculating importance weights and perception weights based on the pre-surveys; performing a general survey process that includes surveying the experience audience to provide a quality rating indicating how well each of the KEAs was delivered based on their own experience; and calculating an Experience Index score as a measure of the quality of the experience that is an aggregation of the received quality ratings weighted by at least one of the importance weights or the perception weights.