Abstract:
A call routing system prompts a caller for information and receives a response from the caller. Based on the caller's response, a confidence value is assigned to the call. The confidence value can be assigned based on the likelihood that the received information is consistent with the prompt and other criteria. Additional prompts are provided to the caller based on the confidence value, and additional caller's responses are used to modify the confidence value. At least one threshold confidence level is set and when the confidence value of the call meets or exceeds the threshold (because of low confidence), the call is immediately routed to a human operator.
Abstract:
A computer-implemented method is described for optimizing prompts for a speech-enabled application. The speech-enabled application is operable to receive communications from a number of users and communicate one or more prompts to each user to illicit a response from the user that indicates the purpose of the user's communication. The method includes determining a number of prompt alternatives (each including one or more prompts) to evaluate and determining an evaluation period for each prompt alternative. The method also includes automatically presenting each prompt alternative to users during the associated evaluation period and automatically recording the results of user responses to each prompt alternative. Furthermore, the method includes automatically analyzing the recorded results for each prompt alternative based on one or more performance criteria and automatically implementing one of the prompt alternatives based on the analysis of the recorded results.
Abstract:
A method for analyzing and adjusting the performance of a speech-enabled application includes selecting a number of user utterances that were previously received by the speech-enabled application. The speech-enabled application receives such user utterances and associates each user utterance with an action-object based on one or more salient terms in the user utterance that are associated with the action-object. The method further includes associating one of a number of action-objects with each of the selected user utterances. Furthermore, for each action-object, the percentage of the utterances associated with the action-object that include at least one of the salient terms associated with the action-object is determined. If the percentage does not exceed a selected threshold, the method also includes adjusting the one or more salient terms associated with the action-object.
Abstract:
A method of identifying and prioritizing automated customer care applications for use in connection with interactive voice response systems is disclosed. The method includes receiving a first set of data produced by a first data-driven evaluation process relating to a call center environment responsive to calls received by the interactive voice response systems; receiving a second set of data produced by a second data-driven evaluation process relating to customer preferences with respect to self-service for each of a set of tasks; and generating a prioritized list of automated customer care applications based on the first set of data and the second set of data.
Abstract:
A system and method of processing a call at a call center is provided. In a particular embodiment, the method includes receiving the call at the call center, receiving an indication element associated with a call center transaction, retrieving call center transaction data based on the indication element, and generating a sequence of pre-populated call center agent terminal transaction processing screens based on at least a portion of the call center transaction data. In a particular embodiment, a set of prioritized transactions based on likelihood of matching a customer request is disclosed.
Abstract:
The disclosure is directed to a system including a factor engine, an audio clip sequencing engine and an announcement engine. The factor engine is configured to identify an ordered set of menu options based on a plurality of weighted factors. The audio clip sequencing engine is responsive to the factor engine and is configured to generate an ordered sequence of audio clips based on the ordered set of menu options. The announcement engine is responsive to the audio clip sequencing engine and is configured to play the ordered sequence of audio clips.
Abstract:
A method of designing a customer interface for a service center, such as an automated speech recognition (ASR) self-service center. Customer activity to an existing service center is monitored, providing customer model, which includes a collection of customer tasks. These tasks are assigned to action-object pairs, which are further assigned to routing destinations. Dialog modules are designed, based on the customer model data, including disambiguation dialogs.
Abstract:
A method of providing a verbal dialog interface for a caller to an automated self-service “how to use” call system. The method uses a combination of natural language and directed dialog techniques to permit callers to hear instructions through three paths: by saying the name of a topic, by selecting the topic from a menu, or by describing the topic. A playback feature permits the caller to control the pace of presentation of the dialog. Partitioning of the dialog into modules ensures that the caller remains on track during the dialog.
Abstract:
A method and system for providing a natural language web site interface. A visitor to the web site (typically a customer to a commercial web site) is prompted to enter a natural language query. The query is interpreted and associated with content for that web site, which is then downloaded to the user.
Abstract:
A computer-implemented method is described for optimizing prompts for a speech-enabled application. The speech-enabled application is operable to receive communications from a number of users and communicate one or more prompts to each user to illicit a response from the user that indicates the purpose of the user's communication. The method includes determining a number of prompt alternatives (each including one or more prompts) to evaluate and determining an evaluation period for each prompt alternative. The method also includes automatically presenting each prompt alternative to users during the associated evaluation period and automatically recording the results of user responses to each prompt alternative. Furthermore, the method includes automatically analyzing the recorded results for each prompt alternative based on one or more performance criteria and automatically implementing one of the prompt alternatives based on the analysis of the recorded results.