Abstract: An apparatus and methods for capturing and analyzing customer interactions the apparatus comprising interaction information units, interaction meta-data information units associated with each of the interaction information units, a rule based analysis engine component for receiving the interaction information, an adaptive database, an interaction capture and storage component for capturing interaction information, a multi segment interaction capture device, an initial set up and calibration device and a pre processing and content extraction device.

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 computerized method of predicting customer churn from an organization, including: receiving at a computer server a recorded customer interaction with an agent of the organization; analyzing the received customer interaction to extract basic features that provide an indication regarding the churn probability of the customer; extracting the entity information of the customer from the recorded interaction; retrieving from a database accessible by the server previous interactions for the same entity and extracting advanced features that provide an indication regarding the churn probability of the customer by comparing multiple interactions of the same entity; predicting a churn probability for the received interaction by applying a statistical customer churn model to the extracted basic features and extracted advanced features; and wherein the interaction and the previous interactions are recordable from more than one type of communication channel by which the customer can communicate with the organization.

Abstract: A method and apparatus for providing real-time assistance related to an interaction associated with a contact center, comprising steps or components for: receiving at least a part of an audio signal of an interaction captured by a capturing device associated with an organization, and metadata information associated with the interaction; performing audio analysis of the at least part of the audio signal, while the interaction is still in progress to obtain audio information; categorizing at least a part of the metadata information and the audio information, to determine a category associated with the interaction, while the interaction is still in progress to obtain audio information; and taking an action associated with the category.

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 spotting a target speaker within a call interaction by generating speaker models based on one or more speaker's speech; and by searching for speaker models associated with one or more target speaker speech files.

Abstract: An apparatus and methods for capturing and analyzing customer interactions the apparatus comprising interaction information units, interaction meta-data information units associated with each of the interaction information units, a rule based analysis engine component for receiving the interaction information, an adaptive database, an interaction capture and storage component for capturing interaction information, a multi segment interaction capture device, an initial set up and calibration device and a pre processing and content extraction device.

Abstract: A method and apparatus for automatically detecting sentiment in interactions. The method and apparatus include training, in which a model is generated upon features extracted from training interactions and tagging information. and run-time in which the model is used towards detecting sentiment in further interactions. The method and apparatus train and use models for classifying context units as containing sentiment or not, the models generated upon tagging data for indicating whether the context units indeed contain sentiment, and the sentiment polarity and intensity within the context unit. A further, upper level model is generated for providing a total score for the interaction, based on the sentiment detected and the classification scores of context units within the interaction.

Abstract: An apparatus and method for an improved audio analysis process is disclosed. The improvement concerns the accuracy level of the results and the rate of false alarms produced by the audio analysis process. The proposed apparatus and method provides a three-stage audio analysis route. The three-stage analysis process includes a pre-analysis stage, a main analysis stage and a post analysis stage.

Abstract: The present invention provides a method and apparatus (100) for capturing and analyzing customer interactions, the apparatus comprising a multi-segment interaction capture device (324), an initial set up and calibration device (326), a pre-processing and context extraction device (328) and a rule-based analysis engine (300).

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 fraud detection method for generating a first fraud or fraud attempt probability, within an at least one captured or recorded interaction, is provided. The method comprises a scoring step for scoring an at least one voice belonging to an at least one tested speaker in the at least one captured or recorded interaction against an at least one voice print within an at least one entry in a voice print collection, the scoring step generating an at least one probability that the at least one voice in the captured or recorded interaction belongs to an at least one second speaker associated with the at least one voice print, said at least one probability represents the probability that the at least one captured or recorded interaction is fraudulent; and an auditing step for auditing the at least one probability and the at least one captured or recorded interaction.

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: A method and apparatus for segmenting an audio interaction, by locating anchor segment from each side of the interaction, iteratively classifying additional segments into one of the two sides, and scoring the resulting segmentation, If the score result is below a threshold, the process is repeated until the segmentation score is satisfactory or until a stopping criterion is met. The anchoring and the scoring steps comprise using additional data associated with the interaction, a speaker thereof, internal or external information related to the interaction or to a speaker thereof or the like.

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: 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 from interactions, broadcasts or other sources. The method and apparatus classify the interactions into predefined categories. Then additional processing is performed on interactions in one or more categories, and analysis is executed for revealing insights, trends, problems, causes for problems, and other characteristics within the one or more categories.

Abstract: A method and apparatus for laughter detection. Laughter is detected through the presence of a sequence of at least a predetermined number such as three consecutive bursts, each burst comprising a voiced portion and an unvoiced portion. After detecting bursts, n-tuples such as triplets are detected, and a likelihood of each burst N-tuple to represent laughter is provided by comparison to predetermined thresholds. Finally, a total score is assigned to the signal based on the grades associated with the triplets and parameters such as the distance between the N-tuples, the total score representing the probability that the audio signal comprises a laughter episode. The method and apparatus preferably comprise a training step and module for determining the thresholds according to manually marked audio signals.