System and method of categorizing communications

• US 10,645,224 B2
• Filed: 04/17/2019
• Issued: 05/05/2020
• Est. Priority Date: 01/08/2014
• Status: Active Grant

• Current Assignee: CallMiner, Inc.
• Original Assignee: CallMiner, Inc.
• Inventors: Dwyer, Michael C., Strand, Erik A., Wolf, Scott R., Salinas, Frank, Gallino, Jeffrey A., Kendrick, Scott A., Xue, Shaoyu
• Primary Examiner(s): Nguyen, Phung-Hoang J
• Application Number:
  US16/386,467
• Publication Number:
  US 20190245971A1
• Time in Patent Office: 384 Days
• CPC Class Codes: G06F 21/6254 by anonymising data, e.g. decorrelating personal data from the owner's identification
• CPC Class Codes: G06F 40/279 Recognition of textual entities
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G10L 15/02 Feature extraction for speech recognition; Selection of recognition unit
• CPC Class Codes: G10L 15/1815 Semantic context, e.g. disambiguation of the recognition hypotheses based on word meaning
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: G10L 15/30 Distributed recognition, e.g. in client-server systems, for mobile phones or network applications
• CPC Class Codes: G10L 2015/088 Word spotting
• CPC Class Codes: G10L 25/72 for transmitting results of analysis
• CPC Class Codes: H04M 2203/301 Management of recordings
• CPC Class Codes: H04M 2203/303 Marking
• CPC Class Codes: H04M 2203/401 Performance feedback
• CPC Class Codes: H04M 2203/551 Call history recording a computer conference H04L12/1831
• CPC Class Codes: H04M 2203/6009 Personal information, e.g. profiles or personal directories being only provided to authorised persons
• CPC Class Codes: H04M 3/42221 Conversation recording systems at the subscriber's set H04M1/656
• CPC Class Codes: H04M 3/5175 Call or contact centers supervision arrangements
• CPC Class Codes: H04M 3/5191 interacting with the Internet

Abstract

A system and method of categorizing communications involves evaluating one or more portions of a communication. Systems include a language module structured to analyze the one or more portions of the communication for at least one of a language characteristic or a non-word symbol within a text of the communication, an acoustic analysis module structured to analyze the one or more portions of the communication for an acoustic characteristic, and a determination module structured to determine at least one category label to associate with the one or more portions of the communication using at least one of the language characteristic or the non-word symbol, and the acoustic characteristic.

Claims

1. A system for evaluating portions of audio communications relating to customer contacts of an enterprise, the system comprising:

a user interface module for receiving enterprise user input to define a language category of a plurality of language categories and an acoustic category of a plurality of acoustic categories to be used to categorize audio communications, wherein the language category is defined by at least one specific language characteristic and the acoustic category is defined by at least one specific acoustic characteristic;

a language module structured to analyze selected portions of the audio communications to determine for the selected portions of the audio communications one or more associated language characteristics, wherein the one or more associated language characteristics are at least one of a presence or absence of specific language, a phoneme, a word, a phrase, a placeholder word used in redaction, or a language pattern;

an acoustic analysis module structured to analyze the selected portions of the audio communications to determine for the selected portions of the audio communications one or more associated acoustic characteristics, wherein the one or more associated acoustic characteristics are at least one of a stress of words, an aggregated stress of a plurality of words, an emphasis, an agitation, a tempo, a change in tempo, a gain in volume or energy of words, a tone, an overtalk, a time lag between words or symbols, a time dependency between key words or phrases, an inter-word timing, an inter-word sequencing, an inter-word distance, an inflexion of words, or a temporal pattern;

a determination module structured to categorize the selected portions of audio communications by determining at least one language category or acoustic category defined by the enterprise user input to associate with each of the selected portions of the audio communications using the determined associated one or more language characteristics and the determined associated one or more acoustic characteristics,

wherein the selected portions of the audio communications are analyzed to determine periods of silence greater than a predetermined length; and

a clustering engine to analyze a content before and after each determined period of silence greater than the predetermined length to determine a topic of the content in order to determine a reason for the period of silence.

2. The system of claim 1, wherein the at least one specific language characteristic is a language pattern comprising an order of occurrence of words.

3. The system of claim 1, wherein the at least one specific language characteristic is a language pattern comprising an order of occurrence of words within a time frame.

4. The system of claim 1, wherein the at least one specific language characteristic is a language pattern comprising a Boolean relationship of words.

5. The system of claim 4, wherein the Boolean relationship is AND, OR, or NOT.

6. The system of claim 1, wherein the at least one specific language characteristic is a language pattern comprising words at a specific location in the selected portions of the audio communications.

7. The system of claim 1, wherein the at least one specific language characteristic is a language pattern comprising a proximity of a topic.

8. The system of claim 1, wherein the at least one language category or acoustic category comprises a combination of one or more other of the plurality of language categories or the plurality of acoustic categories, respectively.

9. The system of claim 1, wherein if no category can be associated with a portion of an audio communication, the determination module is structured to generate a new category and add the new category to a plurality of categories for a subsequent determination.

10. The system of claim 1, wherein the at least one language category is at least one of a behavior, a reason, a procedure, a competitor, a dissatisfaction, an empathy, a repeat contact, a transferred call, a politeness, or a unique label assigned by an enterprise user or the system.

11. The system of claim 10, wherein a numerical weight is user-defined for the at least one language category, a plurality of weights for all categories for the audio communication are aggregated, and a determination is made when the aggregation exceeds a threshold.

12. The system of claim 11, wherein the determination enables tracking progress towards a goal.

13. The system of claim 1, wherein the selected portions of the audio communications are voice communications.

14. The system of claim 13, wherein each voice communication is selected from a group consisting of VoIP, TDM, and SIP.

15. The system of claim 1, wherein the system is adapted to convert the audio communications to text using a computer-based speech recognition module before analyzing the selected portions of the audio communications for the at least one specific language characteristic.

16. The system of claim 1, further comprising a metadata module that acts as a filter to the selected portions of the audio communications, wherein the metadata module further determines a metadata of the audio communications, wherein the metadata is at least one of a speaker name, a speaker type, an agent data, an agent grouping, a call handling location, and a time and date of call.

17. The system of claim 1, further comprising, a contextual module structured to analyze a respective context of a portion of the audio communications, wherein the determination module is further structured to determine the at least one language category or acoustic category associated with that portion using the respective context.

18. The system of claim 17, wherein the contextual module is structured to examine that portion for specific language characteristics or acoustic characteristics that trigger potential contextual relevance to subsequent or prior specific language characteristics or acoustic characteristics of the selected portions of the audio communications.