Method and system for resolving cross-modal references in user inputs

• US 20060143576A1
• Filed: 12/23/2004
• Published: 06/29/2006
• Est. Priority Date: 12/23/2004
• Status: Abandoned Application

• Current Assignee: Motorola, Inc. (Motorola Solutions, Inc.)
• Original Assignee: Motorola, Inc. (Motorola Solutions, Inc.)
• Inventors: Gupta, Anurag K., Anastosakos, Tasos
• Application Number:
  US11/021,237
• Publication Number:
  US 20060143576A1
• Time in Patent Office: Days
• US Class Current: 715/809
• CPC Class Codes: G06F 18/256 of results relating to different input data, e.g. multimodal recognition
• CPC Class Codes: G10L 15/24 Speech recognition using non-acoustical features
• CPC Class Codes: G10L 15/32 Multiple recognisers used in sequence or in parallel; Score combination systems therefor, e.g. voting systems

Abstract

A method and a system for resolving cross-modal references in user inputs to a data processing system (100) are provided. The method includes generating (502) a set of multimodal interpretations (MMIs), based on the user inputs collected during a turn. The set of MMIs includes at least one reference, and each reference includes at least one reference variable. The method further includes generating (504) one or more sets of joint MMIs. Each set of joint MMIs includes MMIs of semantically compatible types. The method further includes generating (506) one or more sets of reference-resolved MMIs, by resolving the reference variables of the references contained in the sets of joint MMIs. The method further includes generating (508) an integrated MMI for each set of reference resolved MMIs. The generation of an integrated MMI is carried out by unifying the MMIs in a set of reference resolved MMIs.

Claims

1. A method for resolving cross-modal references in user inputs to a data processing system, the user inputs being entered through at least one input modality, the method comprising:

generating a set of multimodal interpretations (MMIs) based on the user inputs collected during a turn, at least one MMI comprising at least one reference, each reference comprising at least one reference variable;

generating one or more sets of joint MMIs, each set of joint MMIs comprising MMIs of semantically compatible types;

generating one or more sets of reference resolved MMIs by resolving reference variables of references of the one or more sets of joint MMIs; and

generating an integrated MMI for each set of reference resolved MMIs, wherein the generation of the integrated MMI is done by unifying the set of reference resolved MMIs.

2. The method in accordance with claim 1 further comprising:

generating a type feature structure for each MMI in the set of MMIs; and

identifying the MMIs comprising references from the set of MMIs.

3. The method in accordance with claim 1 wherein resolving the reference variables of references within one or more sets of joint MMIs comprises:

creating one or more reference association structures (RASs), one RAS for each different type of MMI referred to by at least one reference variable of the references within the one set of joint MMIs;

mapping the reference variables of the references within the one set of joint MMIs to the one or more RASs, the mapping being based on the type of MMI required by the reference variable;

sorting the reference variables in each RAS using one or more pre-determined criteria;

mapping each referent, which is an MMI that does not include reference variables, of the one set of joint MMIs to an RAS that has the same type or super-type as the referent;

sorting the referents in each RAS using the one or more pre-determined criteria; and

binding the reference variables in each RAS to one or more referents in the RAS.

4. The method in accordance with claim 3 wherein binding the reference variables in each RAS to one or more referents is done after satisfying any constraints on referents contained in the reference variable.

5. The method in accordance with claim 3 wherein binding referents to the reference variables in each RAS to one or more referents in the RAS comprises associating an aggregate referent with the reference variables.

6. The method in accordance with claim 3 wherein binding referents to the reference variables in each RAS to one or more referents in the RAS comprises associating an unresolved operator with each of one or more reference variables in the RAS when the one or more reference variables are not bound to any referents in the RAS.

7. The method in accordance with claim 3 wherein binding referents to the reference variables in each RAS to one or more referents in the RAS comprises associating a default referent with a reference variable.

8. The method in accordance with claim 5 wherein a default referent is one of a pre-determined value and a value based on the state of the data processing system.

9. The method in accordance with claim 1 wherein a temporal order is put on each of the references within a user turn.

10. The method in accordance with claim 1 wherein each MMI has a time stamp associated with the MMI, the time stamp comprising a start time and an end time of the user input corresponding to the MMI.

11. The method in accordance with claim 10 wherein the reference variables and the referents in the RAS are sorted based on their time stamps.

12. The method in accordance with claim 1 wherein each reference variable comprises information about the type of the referents required to resolve the reference variable.

13. The method in accordance with claim 12 wherein each reference variable refers to a value of an attribute within an MMI that the reference variable is referencing.

14. The method in accordance with claim 12 wherein each reference variable further comprises information about the number of referents required to resolve the reference variable.

15. The method in accordance with claim 12 wherein at least one reference variable further comprises constraints on referents that need to be satisfied by a referent to be bound to the reference variable.

16. A method for resolving cross-modal references in user inputs to a data processing system, the user inputs being entered through at least one input modality, the data processing system generating references based on each user input, each reference comprising at least one reference variable, the method comprising:

collecting multimodal interpretations (MMIs) corresponding to the user inputs for a user turn;

classifying the collected MMIs into one or more sets of semantically compatible MMIs;

identifying MMIs that comprise one or more references in each of the one or more sets of semantically compatible MMIs;

creating one or more reference association structures (RASs) for each set of semantically compatible MMIs, one RAS for each unique type of MMI required to resolve the references in the identified MMIs with the set of semantically compatible MMIs;

mapping the reference variables of the references in the identified MMIs of a set of semantically compatible MMIs to the one or more RASs contained in that set of semantically compatible MMIs, the mapping being based on the type of MMI required by the reference variable;

sorting the reference variables within each RAS using one or more pre-determined criteria;

mapping each referent, which is an MMI that does not have reference variables, of a set of semantically compatible MMIs to an RAS contained in the set of semantically compatible MMIs requiring referents that are of the same type or super type as the referent;

sorting the referents in each RAS using the one or more pre-determined criteria; and

binding the reference variables in each RAS to one or more referents in the RAS.

17. A method for resolving cross-modal references in user inputs to a data processing system, the user inputs being entered through at least one input modality, the data processing system generating references based on each user input, each reference comprising at least one reference variable, the method comprising:

segmenting the user inputs, wherein the segmenting comprises collecting a set of multimodal interpretations (MMIs) corresponding to the user inputs for a user turn;

classifying the collected set of MMIs semantically, wherein semantically classifying the collected set of MMIs comprises creating sets of joint MMIs, each set of joint MMIs comprising MMIs of semantically compatible types;

resolving the reference variables in the sets of joint MMIs to create corresponding sets of reference-resolved MMIs, wherein resolving the reference variables comprises replacing each reference variable with a resolved value; and

integrating the set of reference-resolved MMIs to generate a corresponding set of integrated MMIs.

18. The method in accordance with claim 17 wherein resolving the reference variables comprises:

accessing each set of joint MMIs corresponding to each set of collected and classified MMIs;

building a reference association map, the reference association map comprising at least one RAS corresponding to each unique type of MMI required to resolve the reference variables in the set of joint MMIs and a set of referents corresponding to each RAS;

adding referents to each of the RASs; and

associating referents in the at least one RAS with reference variables in that RAS.

19. The method in accordance with claim 18 wherein building a reference association map comprises:

accessing MMIs in each set of joint MMIs;

adding an accessed MMI to the set of referents if the MMI does not comprise reference variables;

determining whether each reference variable, from an ordered list of reference variables in an accessed MMI, is anaphoric or deictic;

associating a value with a reference variable based on a context, when the reference variable is anaphoric, the context being determined by user inputs acquired in one or more previous turns;

adding a reference variable to the at least one RAS having the same type as the MMI required to satisfy the reference variable when the reference variable is deictic, or when the reference variable is an anaphoric value that cannot be resolved from the context.

20. An electronic equipment that resolves cross-modal references in user inputs to a data processing system, the user inputs being entered through at least one input modality, the equipment comprising:

means for generating a set of multimodal interpretations (MMIs) based on the user inputs collected during a turn, at least one MMI comprising at least one reference, each reference comprising at least one reference variable;

means for generating one or more sets of joint MMIs, each set of joint MMIs comprising MMIs of semantically compatible types;

means for generating a set of reference resolved MMIs for each set of joint MMIs, wherein the generation of the set of reference resolved MMIs is done by resolving reference variables of the references of the set of joint MMIs; and

means for generating an integrated MMI for each set of reference resolved MMIs, wherein the generation of the integrated MMI is done by unifying the set of reference resolved MMIs.

21. A computer program product for use with a computer, the computer program product comprising a computer usable medium having a computer readable program code embodied therein for resolving cross-modal references in user inputs to a data processing system, the user inputs being entered through at least one input modality, the computer program code performing:

generating a set of multimodal interpretations (MMIs) based on the user inputs collected during a turn, at least one MMI comprising at least one reference, each reference comprising at least one reference variable;

generating one or more sets of joint MMIs, each set of joint MMIs comprising MMIs of semantically compatible types;

generating a set of reference resolved MMIs for each set of joint MMIs, wherein the generation of a set of reference resolved MMIs is done by resolving the reference variables of the references of the set of joint MMIs; and

generating an integrated MMI for each set of reference resolved MMIs, wherein the generation of the integrated MMI is done by unifying the set of reference resolved MMIs.