At&t Intellectual Property I, L.p.

At&t Knowledge Ventures, LP

Sbc Properties, L.p.

Sbc Technology Resources, Inc.

Sbc Knowledge Ventures, L.p.

Scott H Mills

Kurt M Joseph

John M Martin

Theodore B Pasquale

Robert Randal Bushey

Benjamin Anthony Knott

James W Miller

James Thomas Miller

Melissa L Oldenburg

Mark A Nixon

James T Miller

In a disclosed method for interpreting automatic speech recognition (ASR) performance data, a data processing system may receive user input that selects a log file to be processed. The log file may contain log records produced by an ASR system as a result of verbal interaction between an individual and the ASR system. In response to receiving the user input, the data processing system may automatically interpret data in the log records and generate interpretation results. The interpretation results may include a duration for a system prompt communicated to the individual by the ASR system, a user response to the system prompt, and a duration for the user response. The user response may include a textual representation of a verbal response from the individual, obtained through ASR. The interpretation results may also include an overall duration for the telephone call.

System and method for analyzing automatic speech recognition performance data

Prioritized user interfaces are disclosed. A user interface may include a menu including a plurality of selectable items displayed in respective menu positions. A menu position of at least one of the plurality of selectable items is assigned based on a prioritization level of the at least one selectable item. The prioritization level is based at least partially on a selection metric for the at least one selectable item. The user interface may also include a menu locator indicating a location of a menu within a multi-level menu structure. The menu locator may include a first indicator of a position within a first level of the multi-level menu structure and a second indicator of a position within a second level of the multi-level menu structure.

Prioritized user interface

A system and method for providing customer activities while in queue allows for one or more customers to interact with one or more customer activities while waiting to speak with a live agent. The customers engage the customer activities while holding in a queue where the customer activities reduce the boredom, frustration, and perceived hold duration associated with holding to speak to a live agent. The customers are offered one or more options of the customer activities to interact with and the system and method monitors the customers' selections and interaction with the customer activities. As agents become available, each customer is transferred to an agent along with information regarding the customer's interaction with a selected customer activity. Upon completion of the interaction between the agent and the customer, the customer has the option to return to the selected customer activity and continue interacting with the selected customer activity.

System and method for providing customer activities while in queue

An interface is provided by creating prompts for the interface. The prompts represent tasks to be accomplished by a user and are obtained based on user input. The prompts are grouped according to relationships, obtained from the user input, among the tasks. The interface is updated based on user feedback. Each of the prompts is designated using user terminology obtained from the user input.

Method and system for automating the creation of customer-centric interfaces

A method of consolidating data from multiple spreadsheets includes selecting multiple spreadsheets (). Portions of data from files corresponding to each of the spreadsheets () are also selected. Automated consolidation of said portions of data is executed. The consolidation includes retrieval of the portions of data, generation of a final report spreadsheet (), and appendage of the portions of data to the final report spreadsheet ().

Flexible multiple spreadsheet data consolidation system

A method and system for automating the analysis of performance data includes an analysis system automatically analyzing a plurality of performance data sets, a task engine, and a score engine. The task engine allows for the matching of each performance data set with an assigned task for each performance data set and the retrieval of a correct key sequence for each performance data set. The score engine compares the correct key sequence with a recorded key sequence of the performance data set to determine if the assigned task is successfully accomplished. The score engine further calculates one or more response times for each performance data set. The automated analysis of performance data allows for a cost savings, more efficient use of time, and more reliable and consistent performance data analysis results.

System and method for the automated analysis of performance data

System and method for providing caller activities while in queue

A method and system for automating the creation of customer-centric interfaces includes a customer-centric interface system automatically creating a customer-centric interface, a collection engine, a customer language engine, a task frequency engine, a customer structure engine, and a customer performance engine. The collection engine collects a plurality of customer intention information. The customer language engine utilizes the customer intention information to create customer-centric menu prompts using the customers own terminology and action specific object words. The task frequency engine determines a frequency of occurrence for the tasks for which the customers contact the customer-centric interface and orders the tasks within the customer-centric interface. The customer structure engine determines how the customers relate the tasks together and groups the tasks according to task relationships. The customer performance engine tests the customer-centric interface and modifies the customer-centric interface for optimal performance.

A system and method for prioritized interface design are disclosed. In one embodiment of a system incorporating teachings of the present disclosure, a wireless-enabled device may include a display, a user input mechanism, and a housing component that at least partially defines an internal cavity. The device may have several engines including a display engine that can initiate presentation of a menu that has several selectable items displayed in respective menu positions. The device may also include a metric engine that tracks some selection metric for the selectable items and a priority engine that determines a prioritization level for the selectable items. In some embodiments, the prioritization level may be related to a selection metric. The device may also have a mapping engine that modifies assigned menu positions for the selectable items in response to changes in the prioritization level of the items.

System and method for prioritized interface design

A method and system for automating the analysis of word frequencies includes a frequency system automatically analyzing a plurality of statements, a count engine, and a cluster engine. The count engine allows for the counting of unique words in the statements and the determination of a frequency of occurrence for each unique word. The frequency system further includes a phrase file allowing for the count engine to specify groups of words as single unique words and a synonym file allowing for the count engine to group one or more words together in synonym groups to be specified as single unique words. The cluster engine locates a plurality of clusters in the statements and determines a cluster frequency of occurrence for each of the clusters. The automated analysis of the statements allows for cost savings, more efficient use of time, and more reliable and consistent word frequency results.

Method and system for automating the analysis of word frequencies

A method and system for evaluating telephone services provided by speech recognition interfaces an evaluation engine with a voice recognition service over a telephone system to submit speech utterance samples to the voice recognition service, receive the response of the voice recognition service to the sample utterances, and determine error and recognition of the sample utterances by the voice recognition service by comparing actual voice recognition service responses to expected responses. The evaluation engine permits evaluation of a voice recognition service for plural glossaries in different contexts, such as through predetermined nodes of a voice recognition service menu having plural glossaries.

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Austin, TX, United States of America

Scott H Mills