Abstract:
A system and method for extracting demographic information from a contact is disclosed. The method discloses: initiating a dialog between a contact and a call handling system; selecting a set of demographic characteristics; assigning a set of acoustic confidence scores; assigning a set of substantive confidence scores; combining the acoustic and substantive confidence scores; and tailoring information presented to the contact using the set of combined confidence scores. The system discloses: an Interactive Voice Response module for initiating a dialog between a contact and a call handling system, and selecting a set of demographic characteristics; an acoustic classifier for assigning a set of acoustic confidence scores; a substantive classifier for assigning a set of substantive confidence scores; and a data combiner for combining the acoustic and substantive confidence scores. The Interactive Voice Response module also tailors information presented to the contact using the set of combined confidence scores.
Abstract:
A method, apparatus, and system are disclosed for computer assisted document analysis. One embodiment is a method for software execution. The method includes selecting, in response to user input, criteria in a character recognition engine to identify suspect errors in scanned documents; executing the engine on a subset of the scanned documents to determine an accuracy of error detection using the criteria; and adjusting, in response to user input, the criteria to adjust the accuracy of identifying suspect errors.
Abstract:
A speech recognition system comprises exactly two automated speech recognition (ASR) engines connected to receive the same inputs. Each engine produces a recognition output, a hypothesis. The system implements one of two (or both) methods for combining the output of the two engines. In one method, a confusion matrix statistically generated for each speech recognition engine is converted into an alternatives matrix in which every column is ordered by highest-to-lowest probability. A program loop is set up in which the recognition outputs of the speech recognition engines are cross-compared with the alternatives matrices. If the output from the first ASR engine matches an alternative, its output is adopted as the final output. If the vectors provided by the alternatives matrices are exhausted without finding a match, the output from the first speech recognition engine is adopted as the final output. In a second method, the confusion matrix for each ASR engine is converted into Bayesian probability matrix.
Abstract:
A system and method for quality of service management within a call handling system is disclosed. The method discloses: initiating a dialog between a contact and an Interactive Voice Response (IVR) module; matching the contact with a predefined contact category; retrieving a predefined quality of service level associated with the contact category; and processing the dialog in accordance with the quality of service level. The system discloses means for effecting the method.
Abstract:
A system and method for language variation guided operator selection is disclosed. The method discloses: initiating a dialog between a contact and a call handling system; identifying a language variation spoken by the contact; determining a skill level with respect to the language variation for each operator within a set of operators; selecting an operator whose skill level in the language variation is above a predetermined value; and transferring the dialog with the contact to the operator. The system discloses means and embodiments for implementing the method.
Abstract:
A system and method for call center dialog management is disclosed. The method discloses: presenting a contact with a first call center dialog segment having a current call center dialog property; receiving from the contact a contact dialog segment; identifying a dialog property keyword within the contact dialog segment; replacing the current call center dialog property with a new call center dialog property in response to the dialog property keyword; and presenting a second call center dialog segment having the new call center dialog property to the contact. The system of the present invention, discloses means for implementing the method.
Abstract:
A system comprises a computer system having a central processing unit coupled to a memory and extraction algorithm. A plurality of different automatic speech recognition (ASR) engines are coupled to the computer system that is adapted to analyze a speech utterance and select one of the ASR engines that will most accurately recognize the speech utterance.
Abstract:
An automated document processing system is configured to normalize zones obtained from a document, and to extract articles from the normalized zones. In one configuration, the system receives at least one zone from the document, and applies at least one zone-breaking factor, thereby creating normalized sub-zones within which text lines are consistent with the at least one zone-breaking factor. The normalized sub-zones may be evaluated to obtain a reading order. Adjacent sub-zones are joined if text similarity exceeds a threshold value. Weakly joined sub-zones are separated where indicated by a topic vectors analysis of the weakly joined sub-zones.
Abstract:
A system comprises a computer system comprising a central processing unit coupled to a memory and resource management application. A plurality of different automatic speech recognition (ASR) engines is coupled to the computer system. The computer system is adapted to select ASR engines to analyze a speech utterance based on resources available on the system.
Abstract:
A method, apparatus, and system are disclosed for computer assisted document modification. One embodiment is a method for software execution. The method automatically extracts articles, in a first phase, from documents to generate different zones of the articles. Different zones of the extracted articles are displayed. In a second phase, plural different zones are manually modified with a document correction tool.