AUTOMATED CALL CLASSIFICATION AND PRIORITIZATION

• US 20090006085A1
• Filed: 06/29/2007
• Published: 01/01/2009
• Est. Priority Date: 06/29/2007
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Kapoor, Ashish, Horvitz, Eric J., Basu, Sumit
• Application Number:
  US11/770,921
• Publication Number:
  US 20090006085A1
• Time in Patent Office: Days
• US Class Current: 704/223
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: G10L 17/00 Speaker identification or verification techniques
• CPC Class Codes: G10L 17/26 Recognition of special voice characteristics, e.g. for use in lie detectors; Recognition of animal voices

Abstract

An automated voice message or caller prioritization system that extracts words, prosody, and/or metadata from a voice input. The data extracted is classified with a statistical classifier into groups of interest. These groups could indicate the likelihood that a call is urgent versus nonurgent, from someone the user knows well versus someone that the user only knows casually or not at all, from someone using a mobile phone versus a landline, or a business call versus a personal calls. The system then can determine an action based on results of the groups, including the display of likely category labels on the message. Call handling and display actions can be defined by user preferences.

Claims

1. A system that determines call features, comprising:

a voice analysis component that classifies a voice file based on at least one of metadata, prosodic features, and key words; and

a decision component that implements an action based on the classification of the voice file.

2. The system of claim 1, further comprising a classifier component that identifies the voice file based on one or more of the source of the voice file and a level of urgency associated with the voice file.

3. The system of claim 2, wherein the call classifier component applies a statistical classifier to classify the voice file.

4. The system of claim 1, further comprising a processor component that translates the voice file into computerized data.

5. The system of claim 1, further comprising a classification component that classifies the voice file into one of a plurality of groups.

6. The system of claim 1, further comprising a call label component that attaches a call label to the voice file.

7. The system of claim 6, further comprising a graphical user interface that displays the call labels.

8. The system of claim 1, further comprising an action determination component that determines the action based at least in part on an identity of the voice file.

9. The system of claim 7, wherein the action determination component determines an action based at least in part on a level of urgency associated with the voice file.

10. The system of claim 1, further comprising a machine learning component that creates a trained model of the voice file based on user preference.

11. The system of claim 1, further comprising a storage component that stores data associated with the voice file.

12. A method of building and using classifiers for voice files, based on the extraction of key evidential features comprising:

analyzing the voice file for predetermined voice input features, the predetermined voice input features including metadata, words or phrases, and prosodic features;

classifying the voice file into one of a plurality of categories; and

determining an action to be taken in response to the voice file.

13. The method of claim 12, wherein the classifying the voice input includes:

identifying the source of the voice input, and

identifying a level of urgency associated with the voice input.

14. The method of claim 12, further comprising implementing machine learning to recognize speech patterns of frequent voice inputs and stores a trained model corresponding to a frequent voice file.

15. The method of claim 12, wherein the (act) includes scrutinizing the voice file and extracting user defined voice file features.

16. The method of claim 12, further comprising labeling the voice file with a classification for the voice file.

17. The method of claim 16, further comprising labeling the voice file with a classification, the classification comprising of one or more of unsolicited, business, personal, urgent, nonurgent, close friend/family, not close friend/family, mobile, and nonmobile.

18. The method of claim 17, further comprising reporting categories to a user interface system based on user preference and probabilities inferred about a set of categories of interest.

19. The method of claim 12, wherein the determining an action includes determining the action based at least in part on a level of urgency in the voice file.

20. A system that determines features of a voice file, comprising:

means for analyzing the voice file for voice input features;

means for recognizing speech patterns using machine learning;

means for classifying voice input into categories; and

means for determining an action in response to voice file.