IP Library › Granted Patent US 11,153,436
Granted Patent B2
US 11,153,436 · App. 16/662,110 · Granted Oct 19, 2021

Automatic nuisance call management

Inventors: Carla Aravena (Winthrop, MA); Sandra Louise Kogan (Newton, MA); Jeffrey Amari (Braintree, MA); Kyle Slachta (Medfield, MA)
Assignee: International Business Machines Corporation
H04M3/4365G10L15/22H04M1/663H04M2201/40
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Quick Facts
Patent No.
US 11,153,436
App. No.
16/662,110
Granted
Oct 19, 2021
Kind
B2
Abstract

The exemplary embodiments disclose a system and method, a computer program product, and a computer system for managing nuisance calls. The exemplary embodiments may include collecting data from a call, extracting one or more features from the collected data, and identifying the call as a nuisance call based on applying one or more models to the extracted one or more features.

Claims (39)

1. A computer-implemented method for managing nuisance calls, the method comprising:

one or more processors collecting data from a call;

extracting two or more features from the collected data, wherein the two or more features include at least one feature selected from a group consisting of caller faceprint and caller fingerprint, and at least one feature selected from a group consisting of delay, inflection, background noise, and static;

identifying the call as a nuisance call based on applying one or more models to the extracted two or more features; and

asking a caller of the call to remove a recipient of the call from a call list based on identifying the call as a nuisance call.

2. The method of claim 1 , wherein the one or more models correlate the one or more features with the likelihood of the call being the nuisance call.

3. The method of claim 1 , further comprising:

receiving feedback indicative of whether the nuisance call was properly identified; and adjusting the model based on the received feedback.

4. The method of claim 1 , further comprising:

prompting the caller of the call to provide a name.

5. The method of claim 4 , further comprising:

determining a call topic, and wherein the one or more extracted features include the call topic.

6. The method of claim 1 , wherein the two the one or more features include features selected from a group comprising a include features selected from a group comprising a name, username, phone number, IP address, MAC address, web address, email

address, geography, serial number, sample audio recording, sample video recording, caller faceprint, caller voiceprint, caller fingerprint, and caller content, delay, silence, tone, inflection, background noise, and static.

7. A computer program product for managing nuisance calls, the computer program product comprising:

one or more non-transitory computer-readable storage media and program instructions stored on the one or more non-transitory computer-readable storage media capable of performing a method, the method comprising:

one or more processors collecting data from a call;

extracting two or more features from the collected data, wherein the two or more features include at least one feature selected from a group consisting of caller faceprint and caller fingerprint, and at least one feature selected from a group consisting of delay, inflection, background noise, and static;

identifying the call as a nuisance call based on applying one or more models to the extracted two or more features; and asking a caller of the call to remove a recipient of the call from a call list based on identifying the call as a nuisance call.

8. The computer program product of claim 7 , wherein the one or more models correlate the one or more features with the likelihood of the call being the nuisance call.

9. The computer program product of claim 7 , further comprising:

receiving feedback indicative of whether the nuisance call was properly identified; and adjusting the model based on the received feedback.

10. The computer program product of claim 7 , further comprising:

prompting the caller of the call to provide a name.

11. The computer program product of claim 10 , further comprising:

determining a call topic, and wherein the one or more extracted features include the call topic.

12. The computer program product of claim 7 , wherein the two the one or more features include features selected from a group comprising a include features selected from a group comprising a name, username, phone number, IP address, MAC address, web address,

email address, geography, serial number, sample audio recording, sample video recording, caller faceprint, caller voiceprint, caller fingerprint, and caller content, delay, silence, tone, inflection, background noise, and static.

13. A computer system for managing nuisance calls, the computer system comprising:

one or more computer processors, one or more computer-readable storage media, and program instructions stored on the one or more of the computer-readable storage media for execution by at least one of the one or more processors capable of performing a method, the method comprising:

one or more processors collecting data from a call;

extracting two or more features from the collected data, wherein the two or more features include at least one feature selected from a group consisting of caller faceprint and caller

fingerprint, and at least one feature selected from a group consisting of delay, inflection, background noise, and static;

identifying the call as a nuisance call based on applying one or more models to the extracted two or more features; and

asking a caller of the call to remove a recipient of the call from a call list based on identifying the call as a nuisance call.

14. The computer system of claim 13 , wherein the one or more models correlate the one or more features with the likelihood of the call being the nuisance call.

15. The computer system of claim 13 , further comprising: receiving feedback indicative of whether the nuisance call was properly identified; and adjusting the model based on the received feedback.

16. The computer system of claim 13 , further comprising:

prompting the caller of the call to provide a name.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 21, 2020
From: ARAVENA, CARLA; KOGAN, SANDRA LOUISE; AMARI, JEFFREY; SLACHTA, KYLE
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 051566/0123 →
Continuity (1)
Related Publication 20210127002A1 · Apr 29, 2021
Cited By (1)
US 12,586,592