Browse Prior Art Database

Monitoring Voice Data for Specific Content Using Unobtrusive Speech Recognition Technology Disclosure Number: IPCOM000030337D
Original Publication Date: 2004-Aug-06
Included in the Prior Art Database: 2004-Aug-06
Document File: 1 page(s) / 33K

Publishing Venue



Call centers often perform quality monitoring. Indeed, many businesses monitor some percentage of inbound / outbound calls to their employees. This is typically done by some sort of pseudo-random, even distribution. A normal statistical quality monitoring system may be in place which records (saves?) the typically statistic samples as normal. This technology can be expanded for additional use in call centers or, in reality, as an adjunct to any telephone switch.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 52% of the total text.

Page 1 of 1

Monitoring Voice Data for Specific Content Using Unobtrusive Speech Recognition Technology

This concept proposes a speech recognition system is attached to the related voice/audio communication channel which monitors 100% of data interactions and takes actions based on key information.

Examples / specifics:

In a call center, maybe the customer says "This is great! Thank you so much!" or related terminology, we record the call and forward it in an email attached as a WAV file to the agent's manager with a subject line of "good job" In a call center or office perhaps the customer says "I'm so disappointed. I want to speak with your manager" we record the call and immediately attempt to conference in a team leader or manager. Maybe on a public or private switch this application listens for keywords like "hack", "bomb", "operation Mickey Mouse", excessive profanity hits, etc. Once triggered, the recording is forwarded to someone to evaluate the recorded call to determine the various party's intent. As part of intelligence gathering for the government/military, sorting through the various data to determine what is worthy of further scrutiny is important - by searching on known key words calls that fit a confidence level could be recorded and evaluated later by an expert - in addition to a normal statistical sampling. The system could initiate a trace to determine ANI / DNIS / caller id / cell phone geographic location, etc. upon hearing specified keywords. Unless the call data triggers an action to co...