Speech-enabled language translation system and method enabling interactive user supervision of translation and speech recognition accuracy

• US 8,239,207 B2
• Filed: 04/15/2009
• Issued: 08/07/2012
• Est. Priority Date: 09/05/2003
• Status: Active Grant

• Current Assignee: ZAMA Innovations LLC
• Original Assignee: Spoken Translation, Inc.
• Inventors: Seligman, Mark, Dillinger, Mike, Friedland, Barton, Cain, Gerald Richard
• Primary Examiner(s): MCFADDEN, SUSAN IRIS
• Application Number:
  US12/424,388
• Publication Number:
  US 20090204386A1
• Time in Patent Office: 1,210 Days
• Field of Search: 704/277
• US Class Current: 704/277
• CPC Class Codes: G06F 40/268 Morphological analysis
• CPC Class Codes: G06F 40/58 Use of machine translation, e.g. for multi-lingual retrieval, for server-side translation for client devices or for real-time translation
• CPC Class Codes: G10L 13/00 Speech synthesis; Text to speech systems
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: G10L 15/30 Distributed recognition, e.g. in client-server systems, for mobile phones or network applications

Abstract

A system and method for a highly interactive style of speech-to-speech translation is provided. The method includes receiving a first and a second language selection and receiving an expression in the first language. The method includes presenting the expression in the first language for verification and translating the verified expression into an expression in the second language. The method further includes confirming the meaning of terms within the verified expression in the first language and back-translating the expression in the second language to a back-translated expression in the first language. The back-translated expression is verified in the first language.

Claims

1. A method for mapping word senses across lexical resources, comprising method operations of:

selecting a target term from a first lexical resource;

identifying a restricted range of possible matches to the target term from a second lexical resource;

calculating a semantic distance between one of the possible matches to the target term;

ranking the possible matches to the target term according to relevance; and

associating the target term from the first lexical resource with one of the possible matches having a lowest semantic distance from the target term, wherein at least one method operation is executed through a processor.

2. The method of claim 1, wherein the method operation of identifying possible matches to the target term from a second lexical resource includes,

identifying word senses of the second lexical resource based on the target term.

3. The method of claim 1, wherein the method operation of identifying possible matches to the target term from a second lexical resource includes,

identifying word senses of the second lexical resource based on Profile terms associated with the target term.

4. The method of claim 1, wherein the method operation of identifying possible matches to the target term from a second lexical resource includes,

identifying word senses of the second lexical resource based on definitions of candidate senses.

5. The method of claim 3, wherein the Profile terms are selected from the group consisting of synonym, hypernyms, hyponyms, and neighboring semantic terms.

6. The method of claim 1, wherein the method operation of identifying possible matches to the target term from a second lexical resource includes,

identifying word senses of the second lexical resource based on component words of the target term.

7. The method of claim 1, wherein the semantic distance represents a degree of similarity between the target term and each of the possible matches.

8. The method of claim 1, wherein the method operation of ranking the possible matches to the target term according to relevance includes,

assigning a weight to each of the possible matches based upon a technique used to associate the target term and respective possible matches.

9. The method of claim 1, wherein the method operation of ranking the possible matches to the target term according to relevance includes,

determining the ranking by a matching technique selected from a group consisting of a target term match, a profile match, a definition match, or a target term component match;

and

extracting a first set of candidates from the target term match technique and a second set of candidates from remaining matching techniques.

10. A non-transitory computer readable medium having program instructions for mapping word senses across lexical resources, comprising:

program instructions for selecting a target term from a first lexical resource;

program instructions for identifying a restricted range of possible matches to the target term from a second lexical resource;

program instructions for calculating a semantic distance between one of the possible matches to the target term;

program instructions for ranking the possible matches to the target term according to relevance; and

program instructions for associating the target term from the first lexical resource with one of the possible matches having a lowest semantic distance from the target term.

11. The computer readable medium of claim 10, wherein the program instructions for identifying possible matches to the target term from a second lexical resource includes,

program instructions for identifying word senses of the second lexical resource based on the target term.

12. The computer readable medium of claim 10, wherein the program instructions for identifying possible matches to the target term from a second lexical resource includes,

program instructions for identifying word senses of the second lexical resource based on Profile terms associated with the target term.

13. The computer readable medium of claim 10, wherein the program instructions for identifying possible matches to the target term from a second lexical resource includes,

program instructions for identifying word senses of the second lexical resource based on definitions of candidate senses.

14. The computer readable medium of claim 12, wherein the Profile terms are selected from the group consisting of synonym, hypernyms, hyponyms, and neighboring semantic terms.

15. The computer readable medium of claim 10, wherein the program instructions for identifying possible matches to the target term from a second lexical resource includes,

program instructions for identifying word senses of the second lexical resource based on component words of the target term.

16. The computer readable medium of claim 10, wherein the semantic distance represents a degree of similarity between the target term and each of the possible matches.

17. The computer readable medium of claim 10, wherein the program instructions for ranking the possible matches to the target term according to relevance includes,

program instructions for assigning a weight to each of the possible matches based upon a technique used to associate the target term and respective possible matches.

18. The computer readable medium of claim 10, wherein the program instructions for ranking the possible matches to the target term according to relevance includes,

program instructions for determining the ranking by a matching technique selected from a group consisting of a target term match, a profile match, a definition match, or a target term component match;

and

program instructions for extracting a first set of candidates from the target term match technique and a second set of candidates from remaining matching techniques.