Surface structure generation

• US 20070067155A1
• Filed: 09/20/2005
• Published: 03/22/2007
• Est. Priority Date: 09/20/2005
• Status: Abandoned Application

• Current Assignee: Sonim Technologies, Inc.
• Original Assignee: Sonim Technologies, Inc.
• Inventors: Newman, Mark, Gurzick, David, Ford, W.
• Application Number:
  US11/231,137
• Publication Number:
  US 20070067155A1
• Time in Patent Office: Days
• US Class Current: 704/9
• CPC Class Codes: G06F 40/237 Lexical tools

Abstract

A deep structure is received. A multistage, surface structure, generation process is used to determine one or more concepts, phrases, and words from the deep structure.

Claims

1. A method comprising:

receiving a deep structure;

determining at least one of (1) one or more concepts, (2) one or more phrases, and (3) one or more words from at least one value in the deep structure; and

determining at least one surface structure from the determined at least one of (1) one or more concepts, (2) one or more phrases, and (3) one or more words from at least one value in the deep structure.

2. The method of claim 1, wherein determining at least one of (1) one or more concepts, (2) one or more phrases, and (3) one or more words from at least one value in the deep structure further comprises:

identifying the at least one value in the deep structure;

searching a data repository for a concept value associated with the at least one is value; and

retrieving the concept value associated with the at least one value in response to identifying the concept value associated with the at least one value from the data repository.

3. The method of claim 2, further comprising:

searching the data repository for at least one phrase value associated with the retrieved concept value; and

retrieving the at least one phrase value associated with the concept value.

4. The method of claim 3, further comprising:

searching the data repository for at least one word value associated with the retrieved at least one phrase value; and

retrieving at least one word associated with the at least one phrase value.

5. The method of claim 4, wherein determining at least one surface structure further comprises:

determining the at least one surface structure from the at least one word.

6. The method of claim 1, wherein determining at least one of (1) one or more concepts, (2) one or more phrases, and (3) one or more words from at least one value in the deep structure further comprises:

determining the (1) one or more concepts, (2) one or more phrases, and (3) one or more words from the at least one value in the deep structure; and

determining at least one surface structure further comprises determining the at least one surface structure from the determined (1) one or more concepts, (2) one or more phrases, and (3) one or more words.

7. The method of claim 6, further comprising:

performing a probabilistic analysis to select at least one of the determined (1) one or more concepts, (2) one or more phrases, and (3) one or more words for generating the at least one surface structure.

8. The method of claim 7, wherein the probabilistic analysis determines a probability that a particular user would use the selected (1) one or more concepts, (2) one or more phrases, and (3) one or more words for generating the at least one surface structure.

9. The method of claim 8, further comprising:

performing a probabilistic analysis to select one surface structure from a plurality of surface structures generated from the determined (1) one or more concepts, (2) one or more phrases, and (3) one or more words.

10. The method of claim 2, wherein identifying the at least one value in the deep structure further comprises:

identifying at least one encoded string value from the received deep structure, wherein the deep structure comprises a reduced, encoded representation of language text.

11. A method comprising:

determining a plurality of values from a deep structure;

for each of the plurality of values

searching a data repository for at least one concept value associated with the value from the deep structure;

identifying the at least one concept value from the data repository, searching the data repository for at least one phrase value associated with the at least one phrase value; and

identifying the at least one phrase value from the data repository, searching the data repository for at least one word associated with the at least one phrase value; and

generating a surface structure from (1) the at least one concept value, (2) the at least one phrase value, and (3) the at least one word.

12. A probabilistic method of determining a surface structure from a deep structure, the method comprising:

receiving a deep structure;

determining a plurality of surface structures from the deep structure; and

performing a probabilistic analysis on each surface structure to select a surface structure from the plurality of surface structures.

13. The method of claim 12, wherein performing a probabilistic analysis on each surface structure further comprises:

determining frequency counts for words;

determining probabilities for each surface structure based on frequency counts for words in each surface structure; and

normalizing the probabilities.

14. The method of claim 13, further comprising:

determining a range of numbers;

assigning a subset of the range of numbers to each surface structure based on the normalized probability for the surface structure, wherein surface structures with higher normalized probabilities have greater amounts of numbers in their subsets;

randomly generating one of the numbers in the range;

determining the surface structure associated with the subset including the randomly generated number; and

selecting the surface structure.

15. The method of claim 13, wherein determining frequency counts for words further comprises:

determining frequency counts for words based on speech patterns for a particular user.

16. The method of claim 12, wherein performing a probabilistic analysis on each surface structure to select a surface structure from the plurality of surface structures further comprises:

assigning probabilities to each surface structure based on speech patterns for a particular user; and

selecting a surface structure based on the assigned probabilities.

17. The method of claim 16, wherein selecting a surface structure based on the assigned probabilities further comprises:

weighting each surface structure, such that surface structures with higher probabilities have higher weights; and

substantially randomly selecting the surface structure, wherein surface structures with higher weights are more likely to be selected.

18. The method of claim 12, wherein determining a plurality of surface structures from the deep structure further comprises:

using a multi-stage generation process operable to determine each surface structure from at least one of concepts, phrases, and words associated with the deep structure.

19. The method of claim 18, wherein using a multi-stage generation process further comprises:

determining a plurality of values from the deep structure;

for each of the plurality of values

searching a data repository for at least one concept value associated with the value from the deep structure;

in response to identifying the at least one concept value from the data repository, searching the data repository for at least one phrase value associated with the at least one phrase value; and

in response to identifying the at least one phrase value from the data repository, searching the data repository for at least one word value associated with the at least one word value; and

generating the surface structure from at least one of (1) the at least one concept value, (2) the at least one phrase value, and (3) the at least one word value.

20. The method of claim 18, further comprising:

performing a probabilistic analysis to select the concepts, the phrases and the words.

21. A surface structure generation system comprising:

a data repository storing concepts, phrases, and words;

a search engine operable to retrieve at least one of concepts, phrases, and words from the data repository associated with a deep structure;

a surface structure generator operable to generate a plurality of surface structures from at least one of concepts, phrases, and words retrieved from the data repository that are associated with the deep structure.

22. The surface structure generation system of claim 21, further comprising:

a probabilistic selector operable to select at least one of the concepts, the phrases, and the words from the data repository based on a probability analysis.

23. The surface structure generation system of claim 22, wherein the probability analysis comprises selecting the at least one of the concepts, the phrases, and the words based on probabilities that a particular user would use the selected at least one of the concepts, the phrases, and the words.

24. The surface structure generation system of claim 22, wherein the probability selector is further operable to select one of the plurality of surface structures based on a probability analysis.

25. The system of claim 21, wherein the data repository stores semantic values for the concepts, phrases, and words and the corresponding concepts, phrases, and words.

26. The system of claim 25, wherein the deep structure comprises a reduced, representation of language text, wherein the semantic values are operable to be used to reduce the language text to the representation.

27. The system of claim 26, wherein the representation is generated using a multi-stage reduction process reducing the language text to concept values, reducing the concept values to phrase values, and reducing the phrase values to word values.

28. The system of claim 21, wherein the surface structure generator operable to perform a multi-stage generation process to generate each surface structure;

wherein the multi-stage generation process includes determining concept values from the deep structure, determining phrase values from the concept values, and determining words from the phrase values.

29. An apparatus comprising:

storage means for storing concepts, phrases, and words;

a search engine means for retrieving at least one of concepts, phrases, and words from the storage means that are associated with a deep structure; and

a surface structure generator means for generating a plurality of surface structures from data retrieved by the search engine means that is associated with the deep structure.

30. The apparatus of claim 29, further comprising:

selection means for performing a probability analysis to select at least one of the concepts, phrases, words, and one of the plurality of surface structures.