System and method for configuring voice readers using semantic analysis

• US 20040260551A1
• Filed: 06/19/2003
• Published: 12/23/2004
• Est. Priority Date: 06/19/2003
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Kumhyr, David Bruce, Janakiraman, Janani, Atkin, Steven Edward
• Application Number:
  US10/464,881
• Publication Number:
  US 20040260551A1
• Time in Patent Office: Days
• US Class Current: 704/260
• CPC Class Codes: G10L 13/04 Details of speech synthesis systems, e.g. synthesiser structure or memory management
• 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

A system and method for using semantic analysis to configure a voice reader is presented. A text file includes a plurality of text blocks, such as paragraphs. Processing performs semantic analysis on each text block in order to match the text block'"'"'s semantic content with a semantic identifier. Once processing matches a semantic identifier with the text block, processing retrieves voice attributes that correspond to the semantic identifier (i.e. pitch value, loudness value, and pace value) and provides the voice attributes to a voice reader. The voice reader uses the text block to produce a synthesized voice signal with properties that correspond to the voice attributes. The text block may include semantic tags whereby processing performs latent semantic indexing on the semantic tags in order to match semantic identifiers to the semantic tags.

Claims

1. A method for text conversion using a computer system, said method comprising:

receiving a text block from a text file;

performing semantic analysis on the text block;

selecting one or more voice attributes based upon the semantic analysis result; and

converting the text block to audio using the selected voice attributes.

2. The method as described in claim 1 wherein at least one of the voice attributes is selected from the group consisting of a pitch value, a loudness value, and a pace value.

3. The method as described in claim 1 wherein the converting further comprises:

providing the selected voice attributes to a voice synthesizer; and

performing the converting using the voice synthesizer.

4. The method as described in claim 3 wherein the providing is performed using an API.

5. The method as described in claim 1 wherein the text file is received from a server, and wherein the server performs the semantic analysis.

6. The method as described in claim 5 wherein the server is adapted to include one or more semantic tags with the text block, the semantic tags corresponding to the semantic analysis result.

7. The method as described in claim 6 further comprising:

extracting one of the semantic tags from the text block;

executing latent semantic indexing on the semantic tag; and

performing the selecting using the results of the latent semantic indexing.

8. The method as described in claim 1 further comprising:

receiving the text file;

identifying one or more section breaks in the text file; and

dividing the text file into a plurality of text blocks using the identified section breaks.

9. The method as described in claim 1 further comprising:

identifying a semantic identifier from a plurality of semantic identifiers in response to the semantic analysis; and

using the semantic identifier to perform the voice attributes selection.

10. The method as described in claim 9 further comprising:

determining whether one or more user interest semantic identifiers are selected; and

wherein the plurality of semantic identifiers includes one or more of the user interest semantic identifiers based upon the determination.

11. The method as described in claim 10 wherein the user interest semantic identifiers are selected from the group consisting of a summary, a detail, a conclusion, and a section heading.

12. The method as described in claim 1 wherein the plurality of semantic identifiers include subject matter semantic identifiers, and wherein at least one of the subject matter semantic identifiers is selected from the group consisting of a children'"'"'s book, a business journal, a male related, a female related, and a teenager related.

13. The method as described in claim 1 wherein the text file is retrieved from a file location, and wherein the file location is selected from the group consisting of a web page server, a computer hard drive, a compact disc, a floppy disc, and a digital video disc.

14. An information handling system comprising:

one or more processors;

a memory accessible by the processors;

one or more nonvolatile storage devices accessible by the processors; and

a text conversion tool to convert text to audio, the text conversion tool comprising software code effective to;

receive a text block from a text file;

perform semantic analysis on the text block;

select one or more voice attributes based upon the semantic analysis result from one of the nonvolatile storage devices; and

convert the text block to speech using the selected voice attributes.

15. The information handling system as described in claim 14 wherein at least one of the voice attributes is selected from the group consisting of a pitch value, a loudness value, and a pace value.

16. The information handling system as described in claim 14 wherein the software code is further effective to:

provide the selected voice attributes to a voice synthesizer; and

use the voice synthesizer to perform the text block conversion.

17. The information handling system as described in claim 16 wherein the voice attributes are provided using an API.

18. The information handling system as described in claim 14 wherein the text file is received from a server, and wherein the server performs the semantic analysis.

19. The information handling system as described in claim 18 wherein the server is adapted to include one or more semantic tags with the text block, the semantic tags corresponding to the semantic analysis result.

20. The information handling system as described in claim 19 wherein the software code is further effective to:

extract one of the semantic tags from the text block;

execute latent semantic indexing on the semantic tag; and

perform the voice attributes selection using the results of the latent semantic indexing.

21. The information handling system as described in claim 14 wherein the software code is further effective to:

receive the text file;

identify one or more section breaks in the text file; and

divide the text file into a plurality of text blocks using the identified section breaks.

22. The information handling system as described in claim 14 wherein the software code is further effective to:

identify a semantic identifier from a plurality of semantic identifiers in response to the semantic analysis; and

use the semantic identifier to perform the voice attributes selection.

23. The information handling system as described in claim 22 wherein the software code is further effective to:

determine whether one or more user interest semantic identifiers are selected; and

wherein the plurality of semantic identifiers includes one or more of the user interest semantic identifiers based upon the determination.

24. The information handling system as described in claim 23 wherein the user interest semantic identifiers are selected from the group consisting of a summary, a detail, a conclusion, and a section heading.

25. The information handling system as described in claim 14 wherein the plurality of semantic identifiers include subject matter semantic identifiers, and wherein at least one of the subject matter semantic identifiers is selected from the group consisting of a children'"'"'s book, a business journal, a male related, a female related, and a teenager related.

26. The information handling system as described in claim 14 wherein the text file is retrieved from a file location, and wherein the file location is selected from the group consisting of a web page server, a computer hard drive, a compact disc, a floppy disc, and a digital video disc.

27. A computer program product stored on a computer operable media for converting text to audio, said computer program product comprising:

means for receiving a text block from a text file;

means for performing semantic analysis on the text block;

means for selecting one or more voice attributes based upon the semantic analysis result; and

means for converting the text block to audio using the selected voice attributes.

28. The computer program product as described in claim 27 wherein at least one of the voice attributes is selected from the group consisting of a pitch value, a loudness value, and a pace value.

29. The computer program product as described in claim 27 wherein the converting further comprises:

means for providing the selected voice attributes to a voice synthesizer; and

means for performing the converting using the voice synthesizer.

30. The computer program product as described in claim 29 wherein the providing is performed using an API.

31. The computer program product as described in claim 27 wherein the text file is received from a server, and wherein the server performs the semantic analysis.

32. The computer program product as described in claim 31 wherein the server is adapted to include one or more semantic tags with the text block, the semantic tags corresponding to the semantic analysis result.

33. The computer program product as described in claim 32 further comprising:

means for extracting one of the semantic tags from the text block;

means for executing latent semantic indexing on the semantic tag; and

means for performing the selecting using the result of the latent semantic indexing.

34. The computer program product as described in claim 27 further comprising:

means for receiving the text file;

means for identifying one or more section breaks in the text file; and

means for dividing the text file into a plurality of text blocks using the identified section breaks.

35. The computer program product as described in claim 27 further comprising:

means for identifying a semantic identifier from a plurality of semantic identifiers in response to the semantic analysis; and

means for using the semantic identifier to perform the voice attributes selection.

36. The computer program product as described in claim 35 further comprising:

means for determining whether one or more user interest semantic identifiers are selected; and

wherein the plurality of semantic identifiers includes one or more of the user interest semantic identifiers based upon the determination.

37. The computer program product as described in claim 36 wherein the user interest semantic identifiers are selected from the group consisting of a summary, a detail, a conclusion, and a section heading.

38. The computer program product as described in claim 27 wherein the plurality of semantic identifiers include subject matter semantic identifiers, and wherein at least one of the subject matter semantic identifiers is selected from the group consisting of a children'"'"'s book, a business journal, a male related, a female related, and a teenager related.

39. The computer program product as described in claim 27 wherein the text file is retrieved from a file location, and wherein the file location is selected from the group consisting of a web page server, a computer hard drive, a compact disc, a floppy disc, and a digital video disc.