Abstract: A method and apparatus of processing caller experiences is disclosed. One example method may include determining a call event type occurring during a call and assigning a weight to the call event type via a processing device. The method may also include calculating a caller experience metric value representing a caller's current call status responsive to determining the at least one call event type, the caller experience metric being a function of the current event type weight and a discounting variable that discounts a value of past events. The method may also provide comparing the caller experience metric to a predefined threshold value and determining whether to perform at least one of transferring the call to a live agent and switching from a current caller modality to a different caller modality.

Abstract: A speech-based system is configured to interact with a user through speech to determine intents and goals of the user. The system may analyze multiple dialog turns in order to determine and fully define a goal that the user is trying to express. Each dialog turn comprises a user utterance. Each dialog turn may also comprise a system speech response. In order to evaluate the performance of the system, logged data is analyzed to identify goal segments within the logged data, where a goal segment is a sequence of dialog turns that relate to a corresponding user goal. A subset of the dialog turns is annotated manually to delineate goal segments. A predictive model is then constructed based on the manually annotated goal segments. The predictive model is then used to identify goal segments formed by additional dialog turns.

Abstract: A method and apparatus of processing communications with end users are disclosed. One example method may include detecting a message or post on a website over the Internet that matches a monitoring company's keywords or rules and processing the message by parsing the message and performing a natural language interpretation of the message and processing the parsed message to determine the user's topic of interest. In response, the method may further provide generating a response to the message based on the user's requested objective and sending the response to the user acknowledging the user's topic of interest. Live agents may be notified to check the status of a message and continually override automated message responses to ensure the integrity of the responses.

Abstract: A method and apparatus of processing caller experiences is disclosed. One example method may include determining a call event type occurring during a call and assigning a weight to the call event type via a processing device. The method may also include calculating a caller experience metric value representing a caller's current call status responsive to determining the at least one call event type, the caller experience metric being a function of the current event type weight and a discounting variable that discounts a value of past events. The method may also provide comparing the caller experience metric to a predefined threshold value and determining whether to perform at least one of transferring the call to a live agent and switching from a current caller modality to a different caller modality.

Abstract: Example embodiments of the present invention may include a method that includes collecting caller response timings to each of a plurality of dialog states conducted during a call, and estimating a plurality of parameters based on the caller response timings. The method may also include selecting a response completeness value responsive to the estimated plurality of parameters, the response completeness value is used to calculate at least one optimal timeout value. The method may also include selecting the at least one optimal timeout value, and setting the at least one optimal timeout value for each of the corresponding dialog states. The timeout value(s) may be used for subsequent calls to provide optimal user satisfaction and call success rates.

Abstract: Example embodiments of the present invention may include a method that provides transcribing spoken utterances occurring during a call and assigning each of the spoken utterances with a corresponding set of first classifications. The method may also include determining a confidence rating associated with each of the spoken utterances and the assigned set of first classifications, and performing at least one of reclassifying the spoken utterances with new classifications based on at least one additional classification operation, and adding the assigned first classifications and the corresponding plurality of spoken utterances to a training data set.

Abstract: A method and apparatus of processing communications with end users are disclosed. One example method may include detecting a message or post on a website over the Internet that matches a monitoring company's keywords or rules and processing the message by parsing the message and performing a natural language interpretation of the message and processing the parsed message to determine the user's topic of interest. In response, the method may further provide generating a response to the message based on the user's requested objective and sending the response to the user acknowledging the user's topic of interest. Live agents may be notified to check the status of a message and continually override automated message responses to ensure the integrity of the responses.

Abstract: A method and apparatus of processing communications with end users are disclosed. One example method may include detecting a message or post on a website over the Internet that matches a monitoring company's keywords or rules and processing the message by parsing the message and performing a natural language interpretation of the message and processing the parsed message to determine the user's topic of interest. In response, the method may further provide generating a response to the message based on the user's requested objective and sending the response to the user acknowledging the user's topic of interest. Live agents may be notified to check the status of a message and continually override automated message responses to ensure the integrity of the responses.

Abstract: Example embodiments of the present invention may include a method that includes collecting caller response timings to each of a plurality of dialog states conducted during a call, and estimating a plurality of parameters based on the caller response timings. The method may also include selecting a response completeness value responsive to the estimated plurality of parameters, the response completeness value is used to calculate at least one optimal timeout value. The method may also include selecting the at least one optimal timeout value, and setting the at least one optimal timeout value for each of the corresponding dialog states. The timeout value(s) may be used for subsequent calls to provide optimal user satisfaction and call success rates.

Abstract: A method and apparatus of processing caller experiences is disclosed. One example method may include determining a call event type occurring during a call and assigning a weight to the call event type via a processing device. The method may also include calculating a caller experience metric value representing a caller's current call status responsive to determining the at least one call event type, the caller experience metric being a function of the current event type weight and a discounting variable that discounts a value of past events. The method may also provide comparing the caller experience metric to a predefined threshold value and determining whether to perform at least one of transferring the call to a live agent and switching from a current caller modality to a different caller modality.

Abstract: A method and apparatus of processing communications with a mobile station are disclosed. One example method may include receiving a message from the mobile station and processing the message by parsing the message and performing a natural language interpretation of the message and processing the parsed message to determine the user's requested objective. In response, the method may further provide generating a response to the message based on the user's requested objective and sending the response to the mobile station acknowledging the user's requested objective. Live agents may be notified to check the status of a message and continually override automated message responses to ensure the integrity of the responses.

Abstract: Example embodiments of the present invention may include a method that provides transcribing spoken utterances occurring during a call and assigning each of the spoken utterances with a corresponding set of first classifications. The method may also include determining a confidence rating associated with each of the spoken utterances and the assigned set of first classifications, and performing at least one of reclassifying the spoken utterances with new classifications based on at least one additional classification operation, and adding the assigned first classifications and the corresponding plurality of spoken utterances to a training data set.

Abstract: A method and apparatus of processing communications with a mobile station are disclosed. One example method may include receiving a message from the mobile station and processing the message by parsing the message and performing a natural language interpretation of the message and processing the parsed message to determine the user's requested objective. In response, the method may further provide generating a response to the message based on the user's requested objective and sending the response to the mobile station acknowledging the user's requested objective. Live agents may be notified to check the status of a message and continually override automated message responses to ensure the integrity of the responses.

Abstract: A method and apparatus of processing communications with end users are disclosed. One example method may include detecting a message or post on a website over the Internet that matches a monitoring company's keywords or rules and processing the message by parsing the message and performing a natural language interpretation of the message and processing the parsed message to determine the user's topic of interest. In response, the method may further provide generating a response to the message based on the user's requested objective and sending the response to the user acknowledging the user's topic of interest. Live agents may be notified to check the status of a message and continually override automated message responses to ensure the integrity of the responses.

Abstract: Example embodiments of the present invention may include a method that provides transcribing spoken utterances occurring during a call and assigning each of the spoken utterances with a corresponding set of first classifications. The method may also include determining a confidence rating associated with each of the spoken utterances and the assigned set of first classifications, and performing at least one of reclassifying the spoken utterances with new classifications based on at least one additional classification operation, and adding the assigned first classifications and the corresponding plurality of spoken utterances to a training data set.

Abstract: A method and apparatus of processing caller experiences is disclosed. One example method may include determining a call event type occurring during a call and assigning a weight to the call event type via a processing device. The method may also include calculating a caller experience metric value representing a caller's current call status responsive to determining the at least one call event type, the caller experience metric being a function of the current event type weight and a discounting variable that discounts a value of past events. The method may also provide comparing the caller experience metric to a predefined threshold value and determining whether to perform at least one of transferring the call to a live agent and switching from a current caller modality to a different caller modality.

Abstract: Example embodiments of the present invention may include a method that includes collecting caller response timings to each of a plurality of dialog states conducted during a call, and estimating a plurality of parameters based on the caller response timings. The method may also include selecting a response completeness value responsive to the estimated plurality of parameters, the response completeness value is used to calculate at least one optimal timeout value. The method may also include selecting the at least one optimal timeout value, and setting the at least one optimal timeout value for each of the corresponding dialog states. The timeout value(s) may be used for subsequent calls to provide optimal user satisfaction and call success rates.

Abstract: Example embodiments of the present invention may include a method that provides transcribing spoken utterances occurring during a call and automatically assigning each of the spoken utterances with a corresponding set of first classifications. The method may also include determining a confidence rating associated with each of the spoken utterances and the assigned set of first classifications, and performing at least one of reclassifying the spoken utterances with new classifications based on at least one additional classification operation, and adding the assigned first classifications and the corresponding plurality of spoken utterances to a training data set.