STATISTICAL MACHINE TRANSLATION FRAMEWORK FOR MODELING PHONOLOGICAL ERRORS IN COMPUTER ASSISTED PRONUNCIATION TRAINING SYSTEM

• US 20140205974A1
• Filed: 12/27/2013
• Published: 07/24/2014
• Est. Priority Date: 06/30/2011
• Status: Abandoned Application

• Current Assignee: Rosetta Stone Limited (Rosetta Stone Incorporated)
• Original Assignee: Rosetta Stone Limited (Rosetta Stone Incorporated)
• Inventors: Pellom, Bryan, Stanley, Theban, Hacioglu, Kadri
• Application Number:
  US14/141,774
• Publication Number:
  US 20140205974A1
• Time in Patent Office: Days
• US Class Current: 434/157
• CPC Class Codes: G06F 40/40 Processing or translation of natural language natural language analysis G06F40/20; semantic analysis G06F40/30
• CPC Class Codes: G09B 19/06 Foreign languages with audible presentation of material to be studied G09B5/04
• CPC Class Codes: G10L 15/063 Training
• CPC Class Codes: G10L 15/187 Phonemic context, e.g. pronunciation rules, phonotactical constraints or phoneme n-grams
• CPC Class Codes: G10L 15/197 Probabilistic grammars, e.g. word n-grams

Abstract

Methods and systems for teaching a user a non-native language include creating models representing phonological errors in the non-native language and generating with the models non-native pronunciations for a native pronunciation. The non-native pronunciations may be used for detecting phonological errors in an utterance spoken in the non-native language by the user. The models can include a native to non-native phone translation model and a non-native phone language model.

Claims

1. A method for teaching a user a non-native language, the method comprising the steps of:

creating, in a computer process, models representing phonological errors in the non-native language; and

generating with the models, in a computer process, non-native pronunciations for a native pronunciation.

2. The method of claim 1, further comprising the step of using the non-native pronunciations for detecting, in a computer process, phonological errors in an utterance spoken in the non-native language by the user.

3. The method of claim 1, wherein the models include a native to non-native phone translation model.

5. The method of claim 1, wherein the models include a non-native phone language model.

6. The method of claim 1, wherein the creating step includes training the models with parallel native pronunciation and non-native pronunciation patterns.

7. The method of claim 6, wherein the parallel native pronunciation and non-native pronunciation patterns respectively include canonical sequences and non-native phone sequences.

8. The method of claim 1, wherein the creating step is performed as a machine translation method.

9. The method of claim 1, wherein the creating step includes aligning native pronunciations with corresponding non-native pronunciations.

10. The method of claim 9, wherein the creating step includes transforming the aligned native and non-native pronunciations into chunks of phone-based alignments, the chunks of phone-based alignments generating a phone translation model.

11. The method of claim 1, wherein the creating step includes using annotated native and non-native phone sequences to generate a non-native phone language model.

4. (canceled)

12. A system for teaching a user a non-native language, the system comprising:

a word aligning module for aligning native pronunciations with corresponding non-native pronunciations, the aligned native and non-native pronunciations for use in creating a native to non-native phone translation model;

a language modeling module for generating a non-native phone language model using annotated native and non-native phone sequences; and

a non-native pronunciation generator for generating non-native pronunciations using the phone translation and phone language models.

13. The system of claim 12, wherein the system is for use with a computer assisted pronunciation training system.

15. The system of claim 12, wherein the system comprises a phonological error modeling system.

17. The system of claim 13, wherein the computer assisted pronunciation training system can be used for non-native speech recognition.

18. The system of claim 12, further comprising a trainer for transforming the aligned native and non-native pronunciations into chunks of phone-based alignments, the chunks of phone-based alignments defining the phone translation model.

19. The system of claim 12, further comprising a speech recognition engine for detecting phonological errors in an utterance spoken in the non-native language by the user.

20. The system of claim 19, wherein the system is for use with a computer assisted pronunciation training system.

22. The system of claim 19, wherein the system comprises a phonological error modeling system.

23. The system of claim 19, wherein the system comprises a computer assisted pronunciation training system.

14. (canceled)

16. (canceled)

21. (canceled)

24. A system for teaching a user a non-native language, the system comprising:

a memory containing instructions;

a processor executing the instructions contained in the memory, the instructions for;

aligning native pronunciations with corresponding non-native pronunciations, the aligned native and non-native pronunciations for use in creating a native to non-native phone translation model;

generating a non-native phone language model using annotated native and non-native phone sequences; and

generating non-native pronunciations using the phone translation and phone language models.

25. (canceled)