System and method of call classification with context modeling based on composite words
First Claim
1. A computer-implemented method of processing and classifying a communication involving at least one human, said method comprising:
- processing by the computer said communication to detect one or more composite words in a given context C, wherein each composite word is a predefined sequence of words S pre-programmed as an atomic unit to prevent partial detection;
estimating a posterior probability P(S|C,X), wherein X is an acoustics vector sequence and wherein said posterior probability P(S|C,X)=P(X|C,S)P(S)/P(X|C,S)+P(X|C,S)), wherein S is an anti model of S;
determining an overall confidence level of events expressed in said one or more composite words occurring in said communication based on said posterior probability; and
classifying said communication into one or more categories based on detected events in accordance with said overall confidence level.
10 Assignments
0 Petitions
Accused Products
Abstract
A system and method of automatically classifying a communication involving at least one human, e.g., a human-to-human telephone conversation, into predefined categories of interest, e.g., “angry customer, etc. The system automatically, or semi-automatically with user interaction, expanding user input into semantically equivalent events. The system recognizes these events, each of which is given a confidence level, and classifies the telephone conversation based on an overall confidence level. In some embodiments, a different base unit is utilized. Instead of recognizing individual words, the system recognizes composite words, each of which is pre-programmed as an atomic unit, in a given context. The recognition includes semantically relevant composite words and contexts automatically generated by the system. The composite words based contextual recognition technique enables the system to efficiently and logically classifying and indexing large volumes of communications and audio collections such as call center calls, Webinars, live news feeds, etc.
-
Citations
37 Claims
-
1. A computer-implemented method of processing and classifying a communication involving at least one human, said method comprising:
-
processing by the computer said communication to detect one or more composite words in a given context C, wherein each composite word is a predefined sequence of words S pre-programmed as an atomic unit to prevent partial detection; estimating a posterior probability P(S|C,X), wherein X is an acoustics vector sequence and wherein said posterior probability P(S|C,X)=P(X|C,S)P(S)/P(X|C,S)+P(X|C,S)), wherein S is an anti model of S; determining an overall confidence level of events expressed in said one or more composite words occurring in said communication based on said posterior probability; and classifying said communication into one or more categories based on detected events in accordance with said overall confidence level. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20)
-
-
21. A system for processing and classifying a communication involving at least one human, said system comprising:
-
means for processing said communication to detect one or more composite words in a given context C, wherein each composite word is a predefined sequence of words S pre-programmed as an atomic unit to prevent partial detection; means for estimating a posterior probability P(S|C,X), wherein X is an acoustics vector sequence and wherein said posterior probability P(S|C,X)=P(X|C,S)P(S)/P(X C,S)+P(X|C,S)), wherein S is an anti model of S; means for determining an overall confidence level of events expressed in said one or more composite words occurring in said communication based on said posterior probability; and means for classifying said communication into one or more categories based on detected events in accordance with said overall confidence level. - View Dependent Claims (22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37)
-
Specification