Computer-aided writing system and method with cross-language writing wizard

• US 7,107,204 B1
• Filed: 04/24/2000
• Issued: 09/12/2006
• Est. Priority Date: 04/24/2000
• Status: Expired due to Term

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Wang, Jian, Liu, Ting, Zhou, Ming
• Primary Examiner(s): CHAWAN, VIJAY B
• Application Number:
  US09/556,229
• Time in Patent Office: 2,332 Days
• Field of Search: 704/9, 704 1- 5, 704/8, 704270-277, 715/531, 715/533, 715/536, 434/157
• US Class Current: 704/2
• CPC Class Codes: G06F 40/232 Orthographic correction, e.g. spell checking or vowelisation
• CPC Class Codes: G06F 40/44 Statistical methods, e.g. probability models
• CPC Class Codes: G06F 40/47 Machine-assisted translation, e.g. using translation memory

Abstract

A computer-aided writing system offers assistance to a user writing in a non-native language, as the user needs help, without requiring the user to divert attention away from the entry task. The writing system provides a user interface (UI) that integrates writing assistance with in-line text entry. When the user is unsure of a word'"'"'s spelling or whether the word is appropriate, the user may enter a corresponding native word directly in line with the ongoing sentence. An error tolerant spelling tool accepts the native word (even if it is misspelled or mistyped) and derives the most probable non-native word for the given context. The spelling tool consults a bilingual dictionary to determine possible non-native word translation candidates, a non-native language model (e.g., a trigram language model) to generate probabilities associated with the candidates given the current sentence or phrase context, and a translation model to generate probabilities of how likely a certain native word was intended given the non-native word candidates. From these probabilities, the spelling tool determines the most probable non-native word translation and substitutes the non-native word for the native input string. If the user likes the non-native word, the user may simply continue with the sentence. On the other hand, if the user is still unsure of the non-native word, the user can invoke a sentence recommendation tool that allows the user to see the non-native word in a bilingual sentence pair to learn how the word can be used.

Claims

1. A computer-implemented method for a providing assistance to a non-native speaker in preparing written text in a native language, the method comprising:

receiving non-native words of a non-native language and at least one native word of a native language that are entered by a user;

identifying at least one non-native word corresponding in meaning to the native word; and

converting the native word to a corresponding non-native word.

2. A method as recited in claim 1, wherein the non-native language is English and the native language is Chinese.

3. A method as recited in claim 1, wherein the non-native words are English words and the native word is Chinese Pinyin.

4. A method as recited in claim 1, wherein the native word is written in phonetic text.

5. A method as recited in claim 1, further comprising displaying the non-native words and the native word within a common entry line.

6. A method as recited in claim 1, wherein the converting comprises determining a most probable non-native word given a context established by the non-native words previously entered by the user.

7. A method as recited in claim 1, wherein the native word is entered in phonetic form, the converting further comprising:

translating the native word from the phonetic form to a language form; and

translating the native word in the language form to the non-native word.

8. A method as recited in claim 1, wherein the native word is entered in phonetic form, the converting further comprising:

determining a most probable language form of the native word and translating the native word from the phonetic form to the most probable language form; and

determining a most probable non-native word given the most probable language form of the native word.

9. A method as recited in claim 1, wherein the native word is entered in phonetic form and the converting comprises translating the native word from the phonetic form to one or more native words in a language form, the method further comprising displaying the one or more native words in the language form.

10. A method as recited in claim 9, further comprising:

displaying the non-native words and the phonetic form of the native word within a common entry line; and

displaying the one or more native words in the language form within a pop-up box adjacent the entry line.

11. A method as recited in claim 10, further comprising ordering the native words within the pop-up box according to probabilities.

12. A method as recited in claim 10, further comprising enabling a user to scroll within the pop-up box.

13. A method as recited in claim 1, wherein the native word is entered in phonetic form and the converting comprises:

translating the native word from the phonetic form to one or more native words in a language form;

displaying the one or more native words in the language form;

translating at least one of the native words in the language form to one or more non-native words; and

displaying the one or more non-native words.

14. A method as recited in claim 13, further comprising:

displaying the non-native words and the phonetic form of the native word within a common entry line; and

displaying the one or more native words in the language form within a pop-Up box adjacent the entry line.

15. A method as recited in claim 13, further comprising:

following translation to the one or more non-native words, displaying the non-native words and the language form of the native word within a common entry line; and

displaying the one or more non-native words within a pop-up box adjacent the entry line.

16. A method as recited in claim 1, further comprising displaying a bilingual sentence pair having a native sentence written in the native language and including the native word and a corresponding non-native sentence written in the non-native language and including the non-native word.

17. One or more computer-readable media having computer-executable instructions that, when executed on a processor, direct a computer to perform the method as recited in claim 1.

18. A computer-based method for providing assistance to a speaker of a second language in preparing written text in a first language, the method comprising:

displaying, via a user interface, character strings in a first language together with at least one character string of a second language as the user enters the character strings;

identifying at least one character string in the first language corresponding in meaning to the character string of the second language;

converting the character string of the second language to an other character string of the first language; and

replacing the character string of the second language with said other character string of the first language in the user interface.

19. A method as recited in claim 18, wherein the first language is English and the second language is Chinese.

20. A method as recited in claim 18, further comprising displaying the character strings of the first and second languages within a common entry line.

21. A method as recited in claim 18, wherein the converting comprises determining a most probable character string given a context established by the character strings previously entered by the user.

22. One or more computer-readable media having computer-executable instructions that, when executed on a processor, direct a computer to perform the method as recited in claim 18.

23. A method comprising:

receiving non-native words of a non-native language and at least one native word of a native language, the native word being received in a first form of the native language;

translating the native word from its first form to at least one native word of a second form; and

translating the native word of the second form to at least one non-native word.

24. A method as recited in claim 23, wherein the non-native language is English and the native language is Chinese.

25. A method as recited in claim 23, wherein the non-native words are English words and the first form of the native word is Chinese Pinyin and the second form of the native word is Chinese Mandarin.

26. A method as recited in claim 23, wherein the translating the native word from its first form comprises selecting a most likely native word of the second form based on statistical probabilities.

27. A method as recited in claim 23, further comprising accepting misspelled versions of the native word in the first form.

28. A method as recited in claim 23, further comprising displaying the non-native words and the native word within a common entry line.

29. A method as recited in claim 23, wherein the translating the native word from its second form to the non-native word comprises:

determining possible non-native word candidates from the second form of the native word;

a generating first probabilities associated with the non-native word candidates that indicate how likely individual non-native word candidates were intended by the user given the context established by previously entered non-native words;

generating second probabilities associated with the non-native word candidates that indicate how likely the second form of the native word was intended given individual non-native word candidates; and

deriving a most probable non-native word from among the non-native word candidates based on the first and second probabilities.

30. A method as recited in claim 23, further comprising replacing the native word in its first form with the non-native word.

31. One or more computer-readable media having computer-executable instructions that, when executed on a processor, direct a computer to perform the method as recited in claim 23.

32. A method comprising:

enabling a user to enter non-native words of a non-native language and a phonetic text string of a native language;

displaying the non-native words and the phonetic text string within a common entry line;

translating the phonetic text string to at least one native word of the native language;

determining possible non-native word candidates from the native word of the native language;

generating first probabilities associated with the non-native word candidates that indicate how likely individual non-native word candidates were intended by the user given the context established by previously entered non-native words;

generating second probabilities associated with the non-native word candidates that indicate how likely the native word was intended given individual non-native word candidates;

deriving a most probable non-native word from among the non-native word candidates based on the first and second probabilities; and

translating the native word to the most probable non-native word.

33. A method as recited in claim 32, wherein the non-native language is English and the native language is Chinese.

34. A method as recited in claim 32, wherein the non-native words are English words, the phonetic text is Chinese Pinyin, and the native word is Chinese Hanzi.

35. A method as recited in claim 32, wherein the translating the phonetic string comprises selecting most likely native words based on statistical probabilities.

36. A method as recited in claim 32, wherein the determining comprises using a bilingual dictionary to identify the non-native word candidates.

37. A method as recited in claim 32, wherein the generating first probabilities comprises using a statistical language model.

38. A method as recited in claim 32, wherein the generating second probabilities comprises using a translation model.

39. A method as recited in claim 32, further comprising displaying the most probable non-native word in place of the phonetic text string.

40. One or more computer-readable media having computer-executable instructions that, when executed on a processor, direct a computer to perform the method as recited in claim 32.

41. A cross-language input user interface for providing assistance to a non-native speaker in preparing written text in a native language, comprising:

a line-based entry area;

non-native text displayed within the line-based entry area;

native text displayed together with the non-native text within the line-based entry area;

indication of the native text to facilitate replacement with non-native text corresponding in meaning to the native next; and

converted non-native text, converted from the native text, substituted for the native text within the line-based entry area.

42. A cross-language input user interface as recited in claim 41, wherein the non-native text comprises English and the native text comprises Chinese.

43. A cross-language input user interface as recited in claim 41, wherein the line-based entry area is oriented horizontally.

44. A cross-language input user interface as recited in claim 41, further comprising a candidate list of non-native words that are possible translations of the native text.

45. A cross-language input user interface as recited in claim 41, further comprising a candidate list of non-native words that are possible translations of the native text, the non-native words being ordered within the candidate list according to a ranking.

46. A cross-language input user interface as recited in claim 41, wherein the line-based entry area is oriented in a first direction and further comprising a candidate list of non-native words that are possible translations of the native text, the candidate list being oriented in a second direction orthogonal to the first direction.

47. A cross-language input user interface as recited in claim 41, further comprising a sentence window, invokable by a user, to present bilingual sentences that include the native text and the non-native text.

48. A word processor comprising the language input user interface as recited in claim 41.

49. A cross-language input user interface for providing assistance to a speaker of a second language In preparing written text in a first language, comprising:

an entry area that accepts first words written in a first language and at least one second word written in a second language;

indication of the second word to facilitate replacement with at least one first word in the first language corresponding in meaning to the second word in the second language; and

a candidate list of first words that are possible translations from the second word.

50. A cross-language input user interface as recited in claim 49, wherein the first language is English and the second language is Chinese.

51. A cross-language input user interface as recited in claim 49, wherein the entry area comprises a line-based entry area oriented in a first direction and the candidate list is presented adjacent the line-based entry area and oriented in a second direction orthogonal to the first direction.

52. A cross-language input user interface as recited in claim 49, further comprising a sentence window, invokable by a user, to present bilingual sentences written in the first and second languages.

53. A word processor comprising the language input user interface as recited in claim 49.

54. A cross-language writing architecture for providing assistance to a non-native sneaker in preparing written text in a native language, comprising;

a user interface to enable a user, who is accustomed to a native language, to;

enter a native word in the native language;

recognize entry of the native word;

provide at least one non-native word corresponding in meaning to the native word;

enter non-native words from a non-native language; and

a spelling tool to assist the user with correct entry of the non-native words.

55. A cross-language writing architecture as recited in claim 54, wherein the user interface allows the user to enter a native word from the native language instead of the non-native word, the spelling tool comprising a translator to translate the native word to a corresponding non-native word.

56. A cross-language writing architecture as recited in claim 55, wherein the translator utilizes a bilingual dictionary.

57. A cross-language writing architecture as recited in claim 55, wherein the translator utilizes a statistical language model.

58. A cross-language writing architecture as recited in claim 55, wherein the translator utilizes a bilingual translation model.

59. A cross-language writing architecture as recited in claim 54, wherein the spelling tool utilizes a thesaurus.

60. A word processor comprising the language input architecture as recited in claim 54.

61. A cross-language writing architecture comprising:

a user interface to enable a user, who is accustomed to a native language, to enter non-native words from a non-native language; and

a sentence recommendation tool to suggest possible sentence structures in the non-native language.

62. A cross-language writing architecture as recited in claim 61, wherein the sentence recommendation tool comprises:

a bilingual corpus containing bilingual sentence pairs written in both the native language and the non-native language; and

a sentence retrieval unit to retrieve bilingual sentence pairs from the bilingual corpus.

63. A cross-language writing architecture as recited in claim 62, wherein the sentence recommendation tool ranks the sentences retrieved from the bilingual corpus.

64. A word processor comprising the language input architecture as recited in claim 61.

65. A cross-language writing architecture comprising:

a user interface to enable entry of English words together with Chinese Pinyin;

a spelling tool to translate the Chinese Pinyin to one or more Chinese words, the spelling tool being further configured to translate the Chinese words to one or more English words that may be substituted for the Chinese Pinyin; and

a sentence recommendation tool, invokable by a user, to offer pairs of corresponding sentences written in English and Chinese to demonstrate how an English word is used in a sentence.

66. A cross-language writing architecture as recited in claim 65, wherein the spelling tool comprises:

a Chinese-English dictionary to determine possible English word candidates from the Chinese words;

an English language model to determine how likely the user intended the English word candidates given previously entered English words; and

an English-Chinese translation model to determine how likely individual Chinese words were intended given the English word candidates.

67. A cross-language writing architecture as recited in claim 65, wherein the sentence recommendation tool comprises:

a bilingual corpus containing bilingual sentence pairs written in both English and Chinese; and

a sentence retrieval unit to retrieve bilingual sentence pairs from the bilingual corpus.

68. A word processor comprising the language input architecture as recited in claim 65.

69. One or more computer-readable media having computer-executable instructions that, when executed on a processor, direct a computer to:

enable entry of English words and Chinese Pinyin;

translate the Chinese Pinyin to at least one Chinese word;

determine possible English word candidates from the Chinese word;

generate first probabilities associated with the English word candidates that indicate how likely each of the English word candidates was intended given previously entered English words;

generate second probabilities associated with the English word candidates that indicate how likely the Chinese word was intended given each of the English word candidates;

derive a most probable English word from among the English word candidates based on the first and second probabilities; and

translate the Chinese word to the most probable English word.