Abstract: Method for managing a promises management apparatus comprises automatically transcribing, using an automatic speech recognition engine, a call between a caller and an agent, based on real-time call stream of the call, wherein the caller calls the agent for resolution of a concern using the promises management apparatus. The method comprises automatically extracting, using a natural language processing engine, in real-time a promise made by the agent to the caller based on the transcript of the call, generating promises data comprising a timeline and an action, and displaying the promises data in a graphical user interface (GUI).

Abstract: A system for categorizing a call between an agent and a caller comprises at least one processor and a memory communicably coupled to the at least one processor. The memory comprises computer executable instructions, which, when executed by the at least one processor implement a method as follows. A call document comprising text of the call between the agent and the caller is received by the system. The system categorizes the call into at least one class using regressive probability analysis of the call document. The system splits the call document to at least two portions, the at least two portions comprising a call header and a call body, and thereafter, using rule-based entity extraction, the system extracts a mandatory entity from the call header and an optional entity from the call body.

Abstract: A method and apparatus for providing an automated workflow guidance to an agent during an active call between the customer and an agent is disclosed. The method includes extracting, at a call analytics server (CAS), from a transcribed text of an audio of a call between a customer and an agent, a call context. The method further includes identifying, by the CAS, at least one workflow based on at least one of the call context, a call metadata, or a historical data, wherein the at least one workflow is identified from a plurality of workflows in a workflow repository remote to the CAS. The identified workflow is sent as guidance from the CAS to a graphical user interface (GUI) accessible by the agent, while the call is active.

Abstract: Method for managing a promises management apparatus comprises automatically transcribing, using an automatic speech recognition engine, a call between a caller and an agent, based on real-time call stream of the call, wherein the caller calls the agent for resolution of a concern using the promises management apparatus. The method comprises automatically extracting, using a natural language processing engine, in real-time a promise made by the agent to the caller based on the transcript of the call, generating promises data comprising a timeline and an action, and displaying the promises data in a graphical user interface (GUI).

Abstract: Method for real-time automated call summarization comprises determining an issue of a caller based on at least one of a call transcript, an extracted intent from the call transcript, or a slot of the intent. Based on the issue, a resolution is determined, and further an action item to implement the resolution is determined. The determined resolution and the action item are displayed in a graphical user interface (GUI).

Abstract: Method for managing a promises management apparatus comprises automatically transcribing, using an automatic speech recognition engine, a call between a caller and an agent, based on real-time call stream of the call, wherein the caller calls the agent for resolution of a concern using the promises management apparatus. The method comprises automatically extracting, using a natural language processing engine, in real-time a promise made by the agent to the caller based on the transcript of the call, generating promises data by assigning an agent, a type, a timeline, an action, and a mode of execution to the promise, and storing the promises data in a datastore.

Abstract: A method and apparatus for guiding an agent during an active call between the customer and an agent is provided. The method comprises extracting, at a call analytics server (CAS), from a transcribed text of an audio of a call between a customer and an agent, a call context. Based on at least one of the call context, a call metadata, or a customer historical data, occurrence of a qualifying event is determined. Upon occurrence of the qualifying event, an action from multiple actions is identified based on at least one of the call context, the call metadata, or the customer historical data. The identified action is sent as guidance from the CAS to a graphical user interface (GUI) accessible by the agent, while the call is active.

Abstract: Method for real-time automated call summarization comprises determining an issue of a caller based on at least one of a call transcript, an extracted intent from the call transcript, or a slot of the intent. Based on the issue, a resolution is determined, and further an action item to implement the resolution is determined. The determined resolution and the action item are displayed in a graphical user interface (GUI).

Abstract: A system for categorizing a call between an agent and a caller comprises at least one processor and a memory communicably coupled to the at least one processor. The memory comprises computer executable instructions, which, when executed by the at least one processor implement a method as follows. A call document comprising text of the call between the agent and the caller is received by the system. The system categorizes the call into at least one class using regressive probability analysis of the call document. The system splits the call document to at least two portions, the at least two portions comprising a call header and a call body, and thereafter, using rule-based entity extraction, the system extracts a mandatory entity from the call header and an optional entity from the call body.

Abstract: Method for real-time automated call summarization comprises determining an issue of a caller based on at least one of a call transcript, an extracted intent from the call transcript, or a slot of the intent. Based on the issue, a resolution is determined, and further an action item to implement the resolution is determined. The determined resolution and the action item are displayed in a graphical user interface (GUI).

Abstract: Method for managing a promises management apparatus comprises automatically transcribing, using an automatic speech recognition engine, a call between a caller and an agent, based on real-time call stream of the call, wherein the caller calls the agent for resolution of a concern using the promises management apparatus. The method comprises automatically extracting, using a natural language processing engine, in real-time a promise made by the agent to the caller based on the transcript of the call, generating promises data by assigning an agent, a type, a timeline, an action, and a mode of execution to the promise, and storing the promises data in a datastore.

Abstract: An analysis system for increasing an efficiency of analysis of customer inputs, is provided. The system includes a structuring module configured to structure a business objective. The system further includes an object of analysis (OA) module configured to enable one or more users to articulate a set of business objectives. The set of business objectives are defined to address a reason for performing the analysis. The system further includes a subject of analysis (SA) module configured to frame a plurality of subjects for each business objective. The plurality of subjects is framed to define each business objective. In addition, the system includes a predicate of analysis (PA) module configured to define a plurality of predicates used to measure each subject. The plurality of predicates employs one or more evaluation modules to measure each subject. Furthermore, the system includes an analysis unit module configured to generate a plurality of analysis units.

Abstract: An adaptive voice authentication system is provided. The adaptive voice authentication system includes an adaptive module configured to compare a feature quality index of the plurality of authentication features and the plurality of enrollment features and dynamically replace and store one or more enrollment features with one or more authentication features to form a plurality of updated enrollment features. The adaptive module is configured to generate an updated enrollment voice print model from the plurality of the updated enrollment features. The adaptive module is further configured to compare the updated enrollment voice print model with the previously stored enrollment voice print model and dynamically update the previously stored enrollment voice print model with the updated enrollment voice print model based on a model quality index.

Abstract: A speech analytics system configured to detect an event is provided. The speech analytics system includes a graphical user interface configured to enable one or more users to upload one or more audio files. The speech analytics system also includes a rules configurator engine configured to receive and store a plurality of event rules. The plurality of event rules are provided by the one or more users via the graphical user interface. Further, the plurality of event rules stored in the rules configurator engine is reconfigurable by the one or more users. In addition, the speech analytics system includes an event detection module coupled to the rules configurator engine and configured to detect the event by processing the audio file. Lastly, the speech analytics system includes an event reporting module configured to notify the event to the one or more users.

Abstract: A voice biometrics system adapted to authenticate a user based on speech diagnostics is provided. The system includes a pre-processing module to receive and pre-process an input voice sample. The pre-processing module includes a clipping module to clip the input voice sample based on a clipping threshold and a voice activity detection module to apply a detection model on the input voice sample to determine an audible region and a non-audible region in the input voice sample. The pre-processing module includes a noise reduction module to apply a noise reduction model to remove noise components from the input voice sample. The voice biometrics system includes a feature extraction module to extract features from the pre-processed input voice sample. The voice biometrics system also includes an authentication module to authenticate the user by comparing a plurality of features extracted from the pre-processed input voice sample to a plurality of enrollment features.

Abstract: A voice biometrics system adapted to authenticate a user based on speech diagnostics is provided. The system includes a pre-processing module to receive and pre-process an input voice sample. The pre-processing module includes a clipping module to clip the input voice sample based on a clipping threshold and a voice activity detection module to apply a detection model on the input voice sample to determine an audible region and a non-audible region in the input voice sample. The pre-processing module includes a noise reduction module to apply a noise reduction model to remove noise components from the input voice sample. The voice biometrics system includes a feature extraction module to extract features from the pre-processed input voice sample. The voice biometrics system also includes an authentication module to authenticate the user by comparing a plurality of features extracted from the pre-processed input voice sample to a plurality of enrolment features.

Abstract: An adaptive voice authentication system is provided. The adaptive voice authentication system includes an adaptive module configured to compare a feature quality index of the plurality of authentication features and the plurality of enrolment features and dynamically replace and store one or more enrolment features with one or more authentication features to form a plurality of updated enrolment features. The adaptive module is configured to generate an updated enrolment voice print model from the plurality of the updated enrolment features. The adaptive module is further configured to compare the updated enrolment voice print model with the previously stored enrolment voice print model and dynamically update the previously stored enrolment voice print model with the updated enrolment voice print model based on a model quality index.