公开(公告)号：US20240211690A1

公开(公告)日：2024-06-27

申请号：US18088261

申请日：2022-12-23

Applicant: Genesys Cloud Services, Inc.

Inventor： Avraham Faizakof ,  Lev Haikin ,  Rotem Maoz ,  Eyal Orbach ,  Nelly David

IPC: G06F40/295 ,  G06V30/19 ,  G10L15/26

CPC classification number: G06F40/295 ,  G06V30/19093 ,  G10L15/26

Abstract: A method for inverse text normalization of contact center communications according to an embodiment includes performing named entity recognition on text from a contact center communication to identify one or more entities in the text, normalizing each of the identified one or more entities in the text using weighted finite-state transducers, and normalizing at least one entity identified in the text using a large language model in response to determining that the at least one entity identified in the text was unable to be normalized using the weighted finite-state transducers.

公开(公告)号：US20250117586A1

公开(公告)日：2025-04-10

申请号：US18378509

申请日：2023-10-10

Applicant: Genesys Cloud Services, Inc.

Inventor： Eyal Orbach ,  Avraham Faizakof ,  Lev Haikin ,  Nelly David ,  Rotem Moaz

IPC: G06F40/30 ,  G06N5/04

Abstract: A system and method of identifying occurrence of a semantic variation of a phrase in a passage by at least one processor may include calculating a phrase embedding vector, representing a semantic meaning of the phrase; extracting, from a textual representation of the passage, at least one hierarchical set of nested sequences of words; for each sequence, calculating a corresponding sequence embedding vector, representing a semantic meaning of the sequence; for one or more sequence embedding vectors, calculating a corresponding vector similarity value, representing similarity of the sequence embedding vectors to the phrase embedding vector, identifying a sequence corresponding to a maximal vector similarity value of the one or more vector similarity values; and determining the identified sequence as a semantic variation of the phrase, based on the maximal vector similarity value.

公开(公告)号：US12001797B2

公开(公告)日：2024-06-04

申请号：US17318524

申请日：2021-05-12

Applicant: GENESYS CLOUD SERVICES, INC.

Inventor： Eyal Orbach ,  Avraham Faizakof ,  Arnon Mazza ,  Lev Haikin

IPC: G06F40/289 ,  G06F16/2458 ,  G06F16/248 ,  G06N3/04

CPC classification number: G06F40/289 ,  G06F16/2468 ,  G06F16/248 ,  G06N3/04

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：US11984116B2

公开(公告)日：2024-05-14

申请号：US17520816

申请日：2021-11-08

Applicant: GENESYS CLOUD SERVICES, INC.

Inventor： Lev Haikin ,  Arnon Mazza ,  Eyal Orbach ,  Avraham Faizakof

IPC: G10L15/197 ,  G06N20/00 ,  G10L15/06 ,  G10L15/10 ,  G10L15/22

CPC classification number: G10L15/197 ,  G06N20/00 ,  G10L15/063 ,  G10L15/10 ,  G10L15/22 ,  G10L2015/0635

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：US20240211701A1

公开(公告)日：2024-06-27

申请号：US18088230

申请日：2022-12-23

Applicant: Genesys Cloud Services, Inc.

Inventor： Lev Haikin ,  Avraham Faizakof ,  Rotem Maoz ,  Eyal Orbach ,  Nelly David

IPC: G06F40/40 ,  G06F40/166 ,  G06F40/279 ,  G10L15/22 ,  G10L15/26

CPC classification number: G06F40/40 ,  G06F40/166 ,  G06F40/279 ,  G10L15/22 ,  G10L15/26

Abstract: A method for generating automatic alternative text suggestions for a speech recognition engine of a contact center system according to an embodiment includes applying a word embedding model to generate a vector representation of each unique word in a contact center communication text corpus, calculating a cosine similarity of each vector representation and each other vector representation generated by the word embedding model, discarding each calculated cosine similarity result determined to be below a predefined threshold to generate a filtered set of word pairs, calculating a Levenshtein distance between words of each word pair of the filtered set of word pairs, and generating a candidate list of alternative words for a target word based on the Levenshtein distance between the words of each word pair of the filtered set of word pairs.