Monitoring, mining, and classifying electronically recordable conversations

• US 7,596,498 B2
• Filed: 09/02/2005
• Issued: 09/29/2009
• Est. Priority Date: 09/02/2005
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Gonzalez de la Fuente, Mauricio, Basu, Sumit
• Primary Examiner(s): MCFADDEN, SUSAN IRIS
• Application Number:
  US11/218,927
• Publication Number:
  US 20070067159A1
• Time in Patent Office: 1,488 Days
• Field of Search: 704/270
• US Class Current: 704/270
• CPC Class Codes: G10L 17/00 Speaker identification or verification techniques
• CPC Class Codes: G10L 25/27 characterised by the analysis technique
• CPC Class Codes: G10L 25/51 for comparison or discrimination
• CPC Class Codes: G10L 25/60 for measuring the quality of voice signals
• CPC Class Codes: H04M 2203/301 Management of recordings
• CPC Class Codes: H04M 2203/559 Sorting systems
• CPC Class Codes: H04M 3/2281 Call monitoring, e.g. for law enforcement purposes; Call tracing; Detection or prevention of malicious calls
• CPC Class Codes: H04M 3/42221 Conversation recording systems at the subscriber's set H04M1/656
• CPC Class Codes: H04M 3/51 Centralised call answering arrangements requiring operator intervention , e.g. call or contact centers for telemarketing

Abstract

Conversations that take place over an electronically recordable channel are analyzed by constructing a set of features from the speech of two participants in the conversation. The set of features is applied to a model or a plurality of models to determine the likelihood of the set of features for each model. These likelihoods are then used to classify the conversation into categories, provide real-time monitoring of the conversation, and/or identify anomalous conversations.

Claims

1. A computer-readable storage medium having computer-executable instructions for performing steps comprising:

generating a feature that is based on speech signals from at least two participants in a conversation held over an electronically recordable channel, the feature comprising a feature from a group of features consisting of;

speaking rate of each participant, energy of speech of each participant, amount of overlapping speech, number of times a different participant begins to speak, number of interruptions, identity of dominant participant, and length of pauses in the speech of the participants;

identifying a deviation between the feature and a conversation model;

applying the deviation to a plurality of deviation models to identify which model best matches the identified deviation; and

classifying the conversation into one of a number of categories based on a label associated with the deviation model that best matches the identified deviation.

2. The computer-readable storage medium of claim 1 further comprising displaying an item that is representative of the value of the feature.

3. The computer-readable storage medium of claim 1 further comprising providing an indication of the classification of the conversation to a monitoring application.

4. The computer-readable storage medium of claim 3 wherein the monitoring application provides visual indications of the classifications of a plurality of conversations.

5. The computer-readable storage medium of claim 4 wherein the visual indications of the classifications of the plurality of conversations are provided while the conversations are in progress.