Abstract: The subject matter discloses a method two phase phonetic indexing and search comprising: receiving a digital representation of an audio signal; producing a phonetic index of the audio signal; producing phonetic N-gram sequence from the phonetic index by segmenting the phonetic index into a plurality of phonetic N-grams; and producing an inverted index of the plurality of phonetic N-grams.

Abstract: The subject matter discloses a computerized method for real time emotion detection in audio interactions comprising: receiving at a computer server a portion of an audio interaction between a customer and an organization representative, the portion of the audio interaction comprises a speech signal; extracting feature vectors from the speech signal; obtaining a statistical model; producing adapted statistical data by adapting the statistical model according to the speech signal using the feature vectors extracted from the speech signal; obtaining an emotion classification model; and producing an emotion score based on the adapted statistical data and the emotion classification model, said emotion score represents the probability that the speaker that produced the speech signal is in an emotional state.

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 system and method for adapting a language model to a specific environment by receiving interactions captured the specific environment, generating a collection of documents from documents retrieved from external resources, detecting in the collection of documents terms related to the environment that are not included in an initial language model and adapting the initial language model to include the terms detected.

Abstract: A computerized method for sales optimization including receiving at a computer server a digital representation of a portion of an interaction between a customer and an organization representative, the portion of an interaction comprises a speech signal of the customer and a speech signal of the organization representative; analyzing the speech signal of the organization representative; analyzing the speech signal of the customer; determining a distance vector between the speech signal of the organization representative and the speech signal of the customer; and predicting a sale success probability score for the captured speech signal portion.

Abstract: The subject matter discloses a computerized method for real time emotion detection in audio interactions comprising: receiving at a computer server a portion of an audio interaction between a customer and an organization representative, the portion of the audio interaction comprises a speech signal; extracting feature vectors from the speech signal; obtaining a statistical model; producing adapted statistical data by adapting the statistical model according to the speech signal using the feature vectors extracted from the speech signal; obtaining an emotion classification model; and producing an emotion score based on the adapted statistical data and the emotion classification model, said emotion score represents the probability that the speaker that produced the speech signal is in an emotional state.

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: The subject matter discloses a method for trade interaction chain reconstruction comprising: identifying a swap deal, the swap deal includes two or more of the received interactions and involves two or more participants; selecting a first interaction of the received interactions, said first interaction involves at least two participants of the two or more participants, said first interaction is stored on a computerized device; obtaining a first plurality of interactions of the received interactions that involve the at least two participants of the two or more participants; determining a first plurality of relevance scores between the first plurality of interactions and the first interaction; and associating interactions of the first plurality of interactions to be relevant to the swap deal according to the determined first plurality of relevance scores.

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: The subject matter discloses a method two phase phonetic indexing and search comprising: receiving a digital representation of an audio signal; producing a phonetic index of the audio signal; producing phonetic N-gram sequence from the phonetic index by segmenting the phonetic index into a plurality of phonetic N-grams; and producing an inverted index of the plurality of phonetic N-grams.

Abstract: The subject matter discloses a computerized method for sales optimization comprising: receiving at a computer server a digital representation of a portion of an interaction between a customer and an organization representative, the portion of an interaction comprises a speech signal of the customer and a speech signal of the organization representative; analyzing the speech signal of the organization representative; analyzing the speech signal of the customer; determining a distance vector between the speech signal of the organization representative and the speech signal of the customer; and predicting a sale success probability score for the captured speech signal portion.

Abstract: A system and method for adapting a language model to a specific environment by receiving interactions captured the specific environment, generating a collection of documents from documents retrieved from external resources, detecting in the collection of documents terms related to the environment that are not included in an initial language model and adapting the initial language model to include the terms detected.

Abstract: A system and method for real-time processing a signal of a voice interaction. In an embodiment, a digital representation of a portion of an interaction may be analyzed in real-time and a segment may be selected. The segment may be associated with a source based on a model of the source. The model may updated based on the segment. The updated model is used to associate subsequent segments with the source. Other embodiments are described and claimed.

Abstract: A transaction verification system and method may include receiving an interaction record describing communications between parties regarding a transaction event. The interaction record may include interactions having multiple communication formats. Transaction data describing transaction parameters input into a trading system during the transaction even may be compared to the interaction record. A matching score may be calculated that indicates a level of similarity between the interaction record and the transaction data. The matching score may be calculated for multiple of transaction events in an interaction log, and an interaction log score may be calculated.

Abstract: A method for automatically detecting sentiments in an audio signal of an interaction held in a call center, including, receiving the audio signal from a logging and capturing unit. Performing audio analysis on the audio signal to obtain text spoken within the interaction. Segmenting the text into context units according to acoustic information acquired from the audio signal to identify units of speech bound by non-speech segments, wherein each context unit includes one or more words. Extracting a sentiment candidate context unit from the context units using a phonetic based search. Extracting linguistic features from the text of the sentiment candidate context unit and acoustic features from a segment of the audio signal associated with the sentiment candidate context unit. Determining in accordance with the linguistic features and acoustic features whether the sentiment candidate context unit is valid or erroneous, and determining sentiment polarity and intensity.

Abstract: A system and method for searching data, such as, text data, using a processing component. A query including one or more terms may be received. At least one term may be automatically added to the query to generate an expanded query set. Entries from one or more information sources, such as, Internet posts, may be retrieved. The retrieved entries may include terms that match terms in the expanded query set. The relevancy of each retrieved entry to the query may be automatically determined. A search result may be provided including a subset of the retrieved entries that are determined to have sufficient relevancy to the query. An output device may display the search result to a client or user.

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: Obtaining information from audio interactions associated with an organization. The information may comprise entities, relations or events. The method comprises: receiving a corpus comprising audio interactions; performing audio analysis on audio interactions of the corpus to obtain text documents; performing linguistic analysis of the text documents; matching the text documents with one or more rules to obtain one or more matches; and unifying or filtering the matches.

Abstract: Retrieving data from audio interactions associated with an organization. Retrieving the data comprises: receiving a corpus containing interactions; performing natural language processing on a text document representing an interaction from the corpus; extracting at least one keyphrase from the text document; assigning a rank to the at least one keyphrase; modeling relations between at least two keyphrases using the rank; and identifying topics relevant for the organization from the relations.