System and method for reverse transliteration using statistical alignment

• US 20050216253A1
• Filed: 03/25/2004
• Published: 09/29/2005
• Est. Priority Date: 03/25/2004
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Brockett, Christopher
• Application Number:
  US10/811,273
• Publication Number:
  US 20050216253A1
• Time in Patent Office: Days
• US Class Current: 704/5
• CPC Class Codes: G06F 40/44 Statistical methods, e.g. probability models
• CPC Class Codes: G06F 40/53 Processing of non-Latin text kana-to-kanji conversion G06F40/129; vowelisation G06F40/232
• 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

Abstract

The present invention obtains a set of word pairs. Each word of the set of word pairs is broken into its component characters, or clusters of commonly co-occurring characters, and using a conventional statistical machine translation algorithm, transliteration models are generated. The transliteration models are used to obtain correct spellings of original language source words from a transliterated form.

Claims

1. A method of training a transliteration processing system, comprising:

receiving a set of word pairs from different languages; and

using statistical textual alignment to align characters of each of the word pairs; and

identifying the transliteration relationships based on the aligned characters.

2. The method of claim 1 wherein receiving a set of word pairs from different languages comprises:

using statistical textual alignment to align words in parallel sentences to form a set.

3. The method of claim 2 wherein receiving a set of word pairs from different languages comprises:

identifying aligned word pairs from the set of sentences.

4. The method of claim 3 and further comprising:

using the transliteration relationships to identify additional word pairs from the set of sentences.

5. The method of claim 1 and further comprising:

calculating an alignment model based on the transliteration relationships identified.

6. The method of claim 5 and further comprising:

receiving an input text; and

generating a transliteration of the input text based on the alignment model.

7. The method of claim 5 wherein calculating the alignment model based on the transliteration relationships identified includes using the context supplied by neighboring characters.

8. A transliteration processing system, comprising

a textual alignment component configured to receive a set of sentences and identify transliteration relationships between words in the set of words based on alignment of characters of the words.

9. The transliteration processing system of claim 8 wherein the textual alignment component is configured to generate an alignment model based on statistical alignment of the characters of the words.

10. The transliteration processing system of claim 9 wherein the textual alignment component is configured to generate the alignment model based on statistical alignment of the characters of the words including using the context supplied by neighboring characters.

11. The transliteration processing system of claim 8 and further comprising:

a text aligning component configured to access a database and align sentences of parallel texts.

12. The transliteration processing system of claim 11 and further comprising:

a data store storing the database.

13. The transliteration processing system of claim 12 wherein the data store is implemented in one or more data stores.

14. The transliteration processing system of claim 8 and further comprising:

a transliteration generator, receiving a textual input and generating a transliteration of the textual input based on the transliteration relationships.

15. A transliteration processing system, comprising:

a transliteration generator receiving a textual input and generating a transliteration of the textual input based on a transliteration relationship received from a textual alignment component configured to receive a set of sentences and identify transliteration relationships between words in the set of sentences based on statistical alignment of characters in the words in the form of machine translation models.