SYSTEM AND METHOD OF UTILIZING A HYBRID SEMANTIC MODEL FOR SPEECH RECOGNITION

• US 20090067590A1
• Filed: 11/11/2008
• Published: 03/12/2009
• Est. Priority Date: 01/14/2005
• Status: Abandoned Application

• Current Assignee: Nuance Communications, Inc. (Microsoft Corporation)
• Original Assignee: SBC Knowledge Ventures LP (AT&T, Inc.)
• Inventors: Knott, Benjamin Anthony, Bushey, Robert R., Martin, John Mills
• Application Number:
  US12/268,894
• Publication Number:
  US 20090067590A1
• Time in Patent Office: Days
• US Class Current: 379/88.140
• CPC Class Codes: G10L 15/08 Speech classification or search
• CPC Class Codes: G10L 15/1815 Semantic context, e.g. disambiguation of the recognition hypotheses based on word meaning
• CPC Class Codes: H04M 2201/60 Medium conversion
• CPC Class Codes: H04M 2203/2011 Service processing based on information specified by a party before or during a call, e.g. information, tone or routing selection
• CPC Class Codes: H04M 3/42204 Arrangements at the exchange for service or number selection by voice at the terminal H04M1/27
• CPC Class Codes: H04M 3/51 Centralised call answering arrangements requiring operator intervention , e.g. call or contact centers for telemarketing

Abstract

A system includes a network interface, a speech input conversion component, and a routing module. Speech input is received in connection with a call. At least a segment of the speech input is transformed into a first textual format. A first list of entries is generated based, at least partially, on consideration of the first textual format. The first list includes at least one action with a corresponding confidence level and at least one object with another corresponding confidence level. An entry of the first list having a higher corresponding confidence level is selected, and a second textual format is output. A second list is generated based, at least partially, on consideration of the selected entry and the second textual format. A routing option is suggested based on the selected entry and a pairing entry in the second list.

Claims

1. A system, comprising:

a network interface configured to receive a speech input in connection with a call;

a speech input conversion component configured to;

transform at least a segment of the speech input into a first textual format;

generate a first list of entries based, at least partially, on consideration of the first textual format, the first list comprising at least one action having a corresponding confidence level and at least one object having another corresponding confidence level;

select an entry of the first list having a higher corresponding confidence level;

output a second textual format;

generate a second list based, at least partially on consideration of the selected entry and the second textual format; and

a routing module configured to suggest a routing option for the call based on the selected entry and an associated pairing entry in the second list.

2. The system of claim 1, wherein the speech input conversion component is further configured to re-process the speech input to create an object list when an action is the selected entry.

3. The system of claim 1, wherein the speech input conversion component is further configured to re-process the speech input to create an action list when an object is the selected entry.

4. The system of claim 2, wherein the speech input conversion component is further configured to:

include an associated confidence level with an object entry in the object list; and

select an object as the pairing entry based on the associated confidence level.

5. The system of claim 3, wherein the speech input conversion component is further configured to:

re-process the speech input to produce the action list with confidence levels; and

select an action based on the confidence levels in the action list.

6. The system of claim 1, wherein the speech input conversion component is further configured to compare the first textual format to a list of word strings and to assign a probability to at least one word string included in the list of word strings.

7. The system of claim 6, wherein the speech input conversion component is further configured to assign an appropriate confidence level to the at least one word string.

8. The system of claim 1, wherein the entry selected is one of a verb and an adverb-verb combination.

9. The system of claim 1, wherein the entry selected is one of a noun or an adjective-noun combination.

10. The system of claim 1, wherein the speech input conversion component is further configured to utilize a synonym table to assist in converting the speech input into action and objects.

11. A method, comprising:

receiving a speech input in connection with a call;

processing the speech input to generate a first action list and an object list;

assigning a first confidence level to each action of the first action list and to each object of the object list;

selecting a particular object with a high confidence level from the object list; and

removing at least one action from the first action list, wherein the at least one action is inconsistent with the particular object.

12. The method of claim 11, further comprising assigning a second confidence level to each remaining action of the first action list based on the particular object.

13. The method of claim 12, further comprising:

re-processing the speech input to generate a second action list;

assigning a second confidence level to each action of the second action list;

selecting a particular action with a high confidence level from the second action list; and

suggesting a routing option for the call based on the particular action and the particular object.

14. The method of claim 13, further comprising routing the call to a destination.

15. The method of claim 13, wherein the first confidence level and the second confidence level are assigned based on a predetermined likelihood of reflecting an intent of a caller.

16. A method, comprising:

receiving a speech input in connection with a call;

processing the speech input to generate a first object list and an action list;

assigning a first confidence level to each object of the first object list and to each action of the action list;

selecting a particular action with a high confidence level from the action list; and

removing at least one object from the first object list, wherein the at least one object is inconsistent with the particular action.

17. The method of claim 16, further comprising assigning a second confidence level to each remaining object of the first object list based on the particular action.

18. The method of claim 17, further comprising:

re-processing the speech input to generate a second object list;

assigning a second confidence level to each object of the second object list; and

selecting a particular object with a high confidence level from the second object list;

suggesting a routing option for the call based on the particular action and the particular object.

19. The method of claim 18, further comprising routing the call to a destination.

20. The method of claim 16, wherein the first confidence level and the second confidence level are assigned based on a predetermined likelihood of reflecting an intent of a caller.