Method and apparatus for preparing a document to be read by a text-to-speech reader

• US 20040059577A1
• Filed: 06/26/2003
• Published: 03/25/2004
• Est. Priority Date: 06/28/2002
• Status: Active Grant

• Current Assignee: Cerence Operating Company (Cerence Inc.)
• Original Assignee: International Business Machines Corporation
• Inventors: Pickering, John B.
• Granted Patent: US 7,490,040 B2
• Time in Patent Office: Days
• US Class Current: 704/260
• CPC Class Codes: G10L 13/08 Text analysis or generation of parameters for speech synthesis out of text, e.g. grapheme to phoneme translation, prosody generation or stress or intonation determination

Abstract

There is disclosed a method and system for preparing a document to be read by a text-to-speech reader. The method can include identifying two or more voice types available to the text-to-speech reader, identifying the text elements within the document, grouping related text elements together, and classifying the text elements according to voice types available to the text-to-speech reader. The method of grouping the related text elements together can include syntactic and intelligent clustering. The classification of text elements can include performing latent semantic analysis on the text elements and characteristics of the available voice types.

Claims

1. A method for preparing a document to be read by a text-to-speech reader, said method comprising:

identifying two or more voice types available to the text-to-speech reader;

identifying text elements within the document;

grouping similar text elements together; and

classifying the text elements according to voice types available to the text-to-speech reader.

2. A method as claimed in claim 1, further comprising marking a text element with a tag corresponding to the voice type classification of the text element.

3. A method as claimed in claim 1, wherein the step of identifying text elements comprises breaking down the document into elements and separating out the text elements.

4. A method as claimed in claim 1, wherein the step of grouping similar text elements together comprises parsing for structural features of the text elements.

5. A method as claimed in claim 4, wherein the structural features of the text elements include at least one of the position of the text element in the document, the syntax of the text element, and text features within the text element.

6. A method as claimed in claim 4, wherein the step of grouping similar text elements further comprises parsing for thematic features of the text elements.

7. A method as claimed in claim 1, wherein the step of classifying the text elements according to the available voice types comprises finding the best match between the grouped text elements and the characteristics of the voice types.

8. A method as claimed in claim 7, wherein the step of classifying the text elements according to the characteristics of the available voice types comprises identifying similar themes within the text elements and voice types.

9. A method as claimed in claim 7, wherein the step of classifying the text elements according to the characteristics of the available voice types comprises identifying similar intentions within the text elements and voice types.

10. A system for preparing a document to be read by a text-to-speech reader, said system comprising:

means for identifying two or more voice types available to the text-to-speech reader;

means for identifying text elements within the document;

means for grouping similar text elements together; and

means for classifying the text elements according to voice types available to the text-to-speech reader.

11. A system as claimed in claim 10, further comprising means for marking a text element with a tag corresponding to the voice type classification of the text element.

12. A system as claimed in claim 10, wherein the means for identifying text elements comprise means for breaking down the document into elements and means for separating out the text elements.

13. A system as claimed in claim 10, wherein the means for grouping similar text elements together comprise means for parsing for structural features of the text elements.

14. A system as claimed in claim 13, wherein the structural features of the text elements include at least one of the position of the text element in the document, the syntax of the text element, and text features within the text element.

15. A system as claimed in claim 13, wherein the means for grouping similar text elements further comprise means for parsing for thematic features of the text elements.

16. A system as claimed in claim 10, wherein the means for classifying the text elements according to the available voice types comprise means for finding the best match between the grouped text elements and the characteristics of the voice types.

17. A system as claimed in claim 16, wherein the means for classifying the text elements according to the characteristics of the available voice types comprise means for identifying similar themes within the text elements and voice types.

18. A system as claimed in claim 16, wherein the means for classifying the text elements according to the characteristics of the available voice types comprise means for identifying similar intentions within the text elements and voice types.

19. A machine readable storage, having stored thereon a computer program having a plurality of code sections executable by a machine for causing the machine to perform the steps of:

identifying two or more voice types available to the text-to-speech reader;

identifying text elements within the document;

grouping similar text elements together; and

classifying the text elements according to voice types available to the text-to-speech reader.

20. A machine readable storage as claimed in claim 19, further causing the machine to perform the step of marking a text element with a tag corresponding to the voice type classification of the text element.

21. A machine readable storage as claimed in claim 19, wherein the step of identifying text elements comprises breaking down the document into elements and code for separating out the text elements.

22. A machine readable storage as claimed in claim 19, wherein the step of grouping similar text elements together comprises parsing for structural features of the text elements.

23. A machine readable storage as claimed in claim 22, wherein the structural features of the text elements include at least one of the position of the text element in the document, the syntax of the text element, and text features within the text element.

24. A machine readable storage as claimed in claim 22, wherein the step of grouping similar text elements further comprises parsing for thematic features of the text elements.

25. A machine readable storage as claimed in claim 19, wherein the step of classifying the text elements according to the available voice types comprises finding the best match between the grouped text elements and the characteristics of the voice types.

26. A machine readable storage as claimed in claim 25, wherein the step of classifying the text elements according to the characteristics of the available voice types comprises identifying similar themes within the text elements and voice types.

27. A machine readable storage as claimed in claim 25, wherein the step of classifying the text elements according to the characteristics of the available voice types comprises identifying similar intentions within the text elements and voice types.