Abstract: A method and system for indicating in real time that an interaction is associated with a problem or issue, comprising: receiving a segment of an interaction in which a representative of the organization participates; extracting a feature from the segment; extracting a global feature associated with the interaction; aggregating the feature and the global feature; and classifying the segment or the interaction in association with the problem or issue by applying a model to the feature and the global feature. The method and system may also use features extracted from earlier segments within the interaction. The method and system can also evaluate the model based on features extracted from training interactions and manual tagging assigned to the interactions or segments thereof.

Abstract: A method and apparatus for automatically sectioning an interaction into sections, in order to get more insight into interactions. The method and apparatus include training, in which a model is generated upon training interactions and available tagging information, and run-time in which the model is used towards sectioning further interactions. The method and apparatus operate on context units within the interaction, wherein each context unit is characterized by a feature vector relate to textual, acoustic or other characteristics of the context unit.

Abstract: A method and apparatus for visualization of call categorization, comprising steps and components for: defining or receiving a definition for one or more categories and criteria for each category; receiving or capturing interactions; categorizing the interactions into the categories; determining relations between the categories; determining layout for the categories and relations; and visualizing the layout. The method and apparatus can further comprise steps and components for extracting key-phrases, determining connections between key-phrases, connections between categories based on key-phrases, and connections between categories and key-phrases, and visualizing the categories, key-phrases and connections. The method and apparatus can further comprise steps and components for training models upon which the relations between categories and relations between key-phrases are determined.

Abstract: A method and apparatus for analyzing and segmenting a vocal interaction captured in a test audio source, the test audio source captured within an environment. The method and apparatus first use text and acoustic features extracted from the interaction with tagging information, for constructing a model. Then, at production time, text and acoustic features are extracted from the interactions, and by applying the model, tagging information is retrieved for the interaction, enabling analysis, flow visualization or further processing of the interaction.

Abstract: A method and apparatus for predicting customer churn from an organization. The method and apparatus determine an interaction churn score based on analyzing an interaction between the customer and the organization and related data. Optionally, the method and apparatus determine also a transactional churn score based on additional data related to the customer or the organization, and a combined churn score based on the interaction churn score and the transactional churn score. The interaction churn score is determined by assessing a categorization score for the interaction in association with one or more categories, and combining the categorization scores. Of further use is a retention offer mechanism for making a retention offer to the customer.

Abstract: In a multi-lingual environment, a method and apparatus for determining a language spoken in a speech utterance. The method and apparatus test acoustic feature vectors extracted from the utterances against acoustic models associated with one or more of the languages. Speech to text is then performed for the language indicated by the acoustic testing, followed by textual verification of the resulting text. During verification, the resulting text is processed by language specific NLP and verified against textual models associated with the language. The system is self-learning, i.e., once a language is verified or rejected, the relevant feature vectors are used for enhancing one or more acoustic models associated with one or more languages, so that acoustic determination may improve.

Abstract: Methods and apparatus for the enhancement of speech to text engines, by providing indications to the correctness of the found words, based on additional sources besides the internal indication provided by the STT engine. The enhanced indications comprise sources of data such as acoustic features, CTI features, phonetic search and others. The apparatus and methods also enable the detection of important or significant keywords found in audio files, thus enabling more efficient usages, such as further processing or transfer of interactions to relevant agents, escalation of issues, or the like. The methods and apparatus employ a training phase in which word model and key phrase model are generated for determining an enhanced correctness indication for a word and an enhanced importance indication for a key phrase, based on the additional features.

Abstract: The disclosed method and apparatus combine interactions and transactions in order to detect fraud acts or fraud attempts. In one embodiment, one or more interactions is correlated with one or more transactions, the interactions is and transactions features are combined, and features are extracted from the combined structure. The features are compared against one or more profiles, and a combined risk score is determined for the interactions or transactions. If the risk score exceeds a predetermined threshold, a preventive/corrective action can be taken. In another embodiment, behavioral characteristics extracted from one or more interactions associated with a transaction, with a risk score obtained by analyzing the transaction. The behavioral characteristic are used to enhance suspicion level related to a transaction being fraudulent, and to enable the taking of measures related to the transaction or to the person handling the transaction.

Abstract: A method and system for indicating in real time that an interaction is associated with a problem or issue, comprising: receiving a segment of an interaction in which a representative of the organization participates; extracting a feature from the segment; extracting a global feature associated with the interaction; aggregating the feature and the global feature; and classifying the segment or the interaction in association with the problem or issue by applying a model to the feature and the global feature. The method and system may also use features extracted from earlier segments within the interaction. The method and system can also evaluate the model based on features extracted from training interactions and manual tagging assigned to the interactions or segments thereof.

Abstract: A method and apparatus for improving speech recognition results for an audio signal captured within an organization, comprising: receiving the audio signal captured by a capturing or logging device; extracting a phonetic feature and an acoustic feature from the audio signal; decoding the phonetic feature into a phonetic searchable structure; storing the phonetic searchable structure and the acoustic feature in an index; performing phonetic search for a word or a phrase in the phonetic searchable structure to obtain a result; activating an audio analysis engine which receives the acoustic feature to validate the result and obtain an enhanced result.

Abstract: A method and apparatus for automatically sectioning an interaction into sections, in order to get more insight into interactions. The method and apparatus include training, in which a model is generated upon training interactions and available tagging information, and run-time in which the model is used towards sectioning further interactions. The method and apparatus operate on context units within the interaction, wherein each context unit is characterized by a feature vector relate to textual, acoustic or other characteristics of the context unit.

Abstract: The disclosed method and apparatus combine interactions and transactions in order to detect fraud acts or fraud attempts. In one embodiment, one or more interactions is correlated with one or more transactions, the interactions is and transactions features are combined, and features are extracted from the combined structure. The features are compared against one or more profiles, and a combined risk score is determined for the interactions or transactions. If the risk score exceeds a predetermined threshold, a preventive/corrective action can be taken. In another embodiment, behavioral characteristics extracted from one or more interactions associated with a transaction, with a risk score obtained by analyzing the transaction. The behavioral characteristic are used to enhance suspicion level related to a transaction being fraudulent, and to enable the taking of measures related to the transaction or to the person handling the transaction.

Abstract: A method and apparatus for indexing one or more audio signals using a speech to text engine and a phoneme detection engine, and generating a combined lattice comprising a text part and a phoneme part. A word to be searched is searched for in the text part, and if not found, or is found with low certainty is divided into phonemes and searched for in the phoneme parts of the lattice.

Abstract: An apparatus and methods for generating an ontology for a domain based on analysis performed on interactions captured in the domain. The analysis provides groups of concepts which are used as topics appearing or retrieved from the interactions are used as topics or concepts in the ontology. Concepts belonging to one group are indicated as connected within the ontology. The ontology can then be used in analyzing further interactions and provide meaning, content and relationships between concepts.

Abstract: In a multi-lingual environment, a method and apparatus for determining a language spoken in a speech utterance. The method and apparatus test acoustic feature vectors extracted from the utterances against acoustic models associated with one or more of the languages. Speech to text is then performed for the language indicated by the acoustic testing, followed by textual verification of the resulting text. During verification, the resulting text is processed by language specific NLP and verified against textual models associated with the language. The system is self-learning, i.e., once a language is verified or rejected, the relevant feature vectors are used for enhancing one or more acoustic models associated with one or more languages, so that acoustic determination may improve.

Abstract: A method and apparatus for visualization of call categorization, comprising steps and components for: defining or receiving a definition for one or more categories and criteria for each category; receiving or capturing interactions; categorizing the interactions into the categories; determining relations between the categories; determining layout for the categories and relations; and visualizing the layout. The method and apparatus can further comprise steps and components for extracting key-phrases, determining connections between key-phrases, connections between categories based on key-phrases, and connections between categories and key-phrases, and visualizing the categories, key-phrases and connections. The method and apparatus can further comprise steps and components for training models upon which the relations between categories and relations between key-phrases are determined.

Abstract: A method and apparatus for analyzing and segmenting a vocal interaction captured in a test audio source, the test audio source captured within an environment. The method and apparatus first use text and acoustic features extracted from the interaction with tagging information, for constructing a model. Then, at production time, text and acoustic features are extracted from the interactions, and by applying the model, tagging information is retrieved for the interaction, enabling analysis, flow visualization or further processing of the interaction.

Abstract: A method and apparatus for predicting customer churn from an organization. The method and apparatus determine an interaction churn score based on analyzing an interaction between the customer and the organization and related data. Optionally, the method and apparatus determine also a transactional churn score based on additional data related to the customer or the organization, and a combined churn score based on the interaction churn score and the transactional churn score. The interaction churn score is determined by assessing a categorization score for the interaction in association with one or more categories, and combining the categorization scores. Of further use is a retention offer mechanism for making a retention offer to the customer.

Abstract: Methods and apparatus for the enhancement of speech to text engines, by providing indications to the correctness of the found words, based on additional sources besides the internal indication provided by the STT engine. The enhanced indications comprise sources of data such as acoustic features, CTI features, phonetic search and others. The apparatus and methods also enable the detection of important or significant keywords found in audio files, thus enabling more efficient usages, such as further processing or transfer of interactions to relevant agents, escalation of issues, or the like. The methods and apparatus employ a training phase in which word model and key phrase model are generated for determining an enhanced correctness indication for a word and an enhanced importance indication for a key phrase, based on the additional features.

Abstract: A method and apparatus for revealing business or organizational aspects of an organization in audio signals captured from interactions, broadcasts or other sources. The method and apparatus activate an efficient process to detect events within the audio signal, and then activate a more resource-consuming additional process around the detected events, thus enhancing efficiency of the process. The detected events and the output of the additional process are analyzed by an analysis process to reveal business aspects, terms, or other events in the audio signal. The analysis results, and possibly the events and output of the additional processing are optionally presented to a user.