Unified call classifier for processing speech and tones as a single information stream

• US 20030083875A1
• Filed: 10/23/2001
• Published: 05/01/2003
• Est. Priority Date: 10/23/2001
• Status: Abandoned Application

• Current Assignee: Danny M. Wages, David J. Skiba, Micheal Kenneth Brown, Norman C. Chan, Sharmistha Sarkar Das
• Original Assignee: Danny M. Wages, David J. Skiba, Micheal Kenneth Brown, Norman C. Chan, Sharmistha Sarkar Das
• Inventors: Brown, Micheal Kenneth, Skiba, David J., Das, Sharmistha Sarkar, Chan, Norman C., Wages, Danny M.
• Application Number:
  US10/037,584
• Publication Number:
  US 20030083875A1
• Time in Patent Office: Days
• US Class Current: 704/249
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: H04M 2201/40 using speech recognition
• CPC Class Codes: H04M 2203/2027 Live party detection
• CPC Class Codes: H04M 3/2218 Call detail recording
• CPC Class Codes: H04M 3/42314 in private branch exchanges
• CPC Class Codes: H04M 3/436 Arrangements for screening incoming calls , i.e. evaluating the characteristics of a call before deciding whether to answer it based on the calling party profile H04M3/42059; based on location H04M3/42348; based on presence H04M3/42365; diversion H04M3/54
• CPC Class Codes: H04Q 1/444 with voice-band signalling frequencies

Abstract

Classifying a call to a called destination endpoint by a call classifier. The call classifier is responsive to information received from the called destination endpoint to perform the call classification.

Claims

1. A method for doing call classification on a call to a destination endpoint, comprising the steps of:

receiving audio information from the destination endpoint;

concurrently analyzing using automatic speech recognition the received audio information for a first type of classification and a second type of classification; and

determining a call classification for the destination endpoint in response to the step of analyzing.

2. The method of claim 1 wherein the first type of classification is for words.

3. The method of claim 2 wherein the analyzed words are formed as phrases.

4. The method of claim 2 wherein the second type of classification is for tones.

5. The method of claim 4 wherein the step of analyzing comprises the step of executing a Hidden Markov Model to determine the presence of words or tones in the audio information.

6. The method of claim 5 wherein the step of executing comprises the step of using a grammar for speech and tones.

7. The method of claim 6 wherein the step of determining comprises the step of executing an inference engine.

8. A method for doing call classification on a call to a destination endpoint, comprising the steps of:

receiving audio information from the destination endpoint;

concurrently analyzing using automatic speech recognition the received audio information for words and tones; and

determining a call classification for the destination endpoint in response to the analysis for words and tones.

9. The method of claim 8 wherein the step of analyzing for speech comprises the step of executing a Hidden Markov Model to determine the presence of words or tones in the audio information.

10. The method of claim 9 wherein the step of executing comprises the step of using a grammar for speech and tones.

11. The method of claim 10 wherein the step of determining comprises the step of executing an inference engine.

12. A method for doing call classification by an automatic speech recognition unit on a call to a destination endpoint, comprising the steps of:

receiving audio information from the destination endpoint by the automatic speech recognition unit;

concurrently analyzing using automatic speech recognition the received audio information for a first type of classification and a second type of classification by the automatic speech recognition unit; and

determining a call classification for the destination endpoint in response to the step of analyzing by the automatic speech recognition unit.

13. The method of claim 12 wherein the first type of classification is for words.

14. The method of claim 13 wherein the analyzed words are formed as phrases.

15. The method of claim 13 wherein the second type of classification is for tones.

16. The method of claim 15 wherein the step of analyzing comprises the step of executing a Hidden Markov Model to determine the presence of words or tones in the audio information.

17. The method of claim 16 wherein the step of executing comprises the step of using a grammar for speech and tones.

18. The method of claim 17 wherein the step of determining comprises the step of executing an inference engine.

19. A call classifier for determining the call classification of a called destination endpoint, comprising:

an automatic speech recognizer for detecting first and second characteristics in audio information received from the called destination endpoint; and

inference engine for classifying the call in response to the automatic speech recognizer.

20. The call classifier of claim 19 wherein the first characteristics are words.

21. The call classifier of claim 20 wherein the words are formed into phrases.

22. The call classifier of claim 20 wherein the second characteristics are tones.

23. The call classifier of claim 22 wherein the automatic speech recognizer is executing a Hidden Markov Model.