IP Library Granted Patent US 7,562,005
Granted Patent B1
US 7,562,005 · App. 11/689,749 · Granted Jul 14, 2009

System and method for natural language generation

View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 7,562,005
App. No.
11/689,749
Granted
Jul 14, 2009
Kind
B1
Abstract

A system, method and computer-readable medium for generating natural language utilizes a stochastic process to choose a derivation tree according to a predetermined grammar, such as tree-adjoined grammar (TAG). A word lattice is created from a single semi-specified derivation tree and the proper path (i.e., desired output string) is selected from the lattice using a least cost, or other appropriate algorithms.

Claims (37)

1. A method for generating natural language output, the method comprising:

executing instructions in a computing device to create a semi-specified derivation tree by selecting tree-adjoining grammar trees for each node in an input dependency syntax tree;

executing instructions in a computing device to create a lattice of all possible linearizations of the selected tree-adjoining grammar trees; and

executing instructions in a computing device to generate natural language output by selecting a most likely traversal path through the created lattice.

2. The method of claim 1 , wherein the step of selecting tree-adjoining grammar trees utilizes a tree model database.

3. The method of claim 1 , wherein the lattice is created using a reference grammar.

4. The method of claim 3 , wherein the reference grammar is from a reference grammar database comprising an XTAG grammar database.

5. The method of claim 1 , wherein:

the step of selecting tree-adjoining grammar trees is performed by a tree choosing module;

the step of creating a lattice is performed by an unraveling module; and

the step of selecting a most likely traversal path is performed by a linear precedence chooser module.

6. The method of claim 1 , wherein selecting a most likely traversal path utilizes a Viterbi algorithm.

7. A tangible computer-readable medium storing instructions for controlling a computing device to generate natural language output, the instructions comprising:

creating a semi-specified derivation tree by selecting tree-adjoining grammar trees for each node in an input dependency syntax tree;

creating a lattice of all possible linearizations of the trees using a reference grammar; and

generating natural language output by selecting a most likely traversal path through the created lattice.

8. The tangible computer-readable medium of claim 7 , wherein the step of selecting tree-adjoining grammar trees utilizes a tree model database.

9. The tangible computer-readable medium of claim 7 , wherein the lattice is created using a reference grammar.

10. The tangible computer-readable medium of claim 9 , wherein the reference grammar is from a reference grammar database comprising an XTAG grammar database.

11. The tangible computer-readable medium of claim 7 , wherein:

the step of selecting tree-adjoining grammar trees is performed by a tree choosing module;

the step of creating a lattice is performed by an unraveling module; and

the step of selecting a most likely traversal path is performed by a linear precedence chooser module.

12. The tangible computer-readable medium of claim 7 , wherein selecting a most likely traversal path utilizes a Viterbi algorithm.

13. A computing device for generating a natural language output, the computing device comprising:

the processor;

a module configured to control the computer device to create a semi-specified derivation tree by selecting tree-adjoining grammar trees for each node in an input dependency syntax tree;

a module configured to control the computing device to create a lattice of all possible linearizations of the selected tree-adjoining grammar trees; and

a module configured to control the computing device to generate natural language output by selecting a most likely traversal path through the created lattice.

14. The computing device of claim 13 , wherein the module configured to control the computing device to select tree-adjoining grammar trees utilizes a tree model database.

15. The computing device of claim 13 , wherein the lattice is created using a reference grammar.

16. The computing device of claim 15 , wherein the reference grammar is from a reference grammar database comprising an XTAG grammar database.

17. The computing device of claim 13 , wherein:

the module configured to control the computing device to select tree-adjoining grammar trees is a tree choosing module;

the module configured to control the computing device to create a lattice is an unraveling module; and

the module configured to control the computing device to select a most likely traversal path is a linear precedence chooser module.

18. The computing device of claim 13 , wherein the module configured to control the computing device to select a most likely traversal path utilizes a Viterbi algorithm.

Assignments (4)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 26, 2017
From: AT&T INTELLECTUAL PROPERTY II, L.P.
To: NUANCE COMMUNICATIONS, INC.
Reel/Frame 041512/0608 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 26, 2016
From: AT&T CORP.
To: AT&T PROPERTIES, LLC
Reel/Frame 038529/0164 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 26, 2016
From: AT&T PROPERTIES, LLC
To: AT&T INTELLECTUAL PROPERTY II, L.P.
Reel/Frame 038529/0240 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 30, 2016
From: BANGALORE, SRINIVAS; RAMBOW, OWEN CHRISTOPHER
To: AT&T CORP.
Reel/Frame 038137/0462 →