Multilingual text-to-speech system with limited resources

• US 20050182630A1
• Filed: 02/02/2004
• Published: 08/18/2005
• Est. Priority Date: 02/02/2004
• Status: Active Grant

• Current Assignee: Sovereign Peak Ventures, LLC (Dominion Harbor Enterprises, LLC)
• Original Assignee: Panasonic Corporation (Panasonic Holdings Corporation)
• Inventors: Junqua, Jean-Claude, Veprek, Peter, Miro, Xavier Anguera
• Granted Patent: US 7,596,499 B2
• Time in Patent Office: Days
• US Class Current: 704/269
• 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 multilingual text-to-speech system includes a source datastore of primary source parameters providing information about a speaker of a primary language. A plurality of primary filter parameters provides information about sounds in the primary language. A plurality of secondary filter parameters provides information about sounds in a secondary language. One or more secondary filter parameters is normalized to the primary filter parameters and mapped to a primary source parameter.

Claims

1. A multilingual text-to-speech system, comprising:

a source datastore of primary source parameters providing information mainly about a speaker of a primary language;

a plurality of primary filter parameters providing information mainly about sounds in the primary language; and

a plurality of secondary filter parameters providing information mainly about sounds in a secondary language, wherein at least one secondary filter parameter is normalized to the primary filter parameters and mapped to a primary source parameter.

2. The system of claim 1, further comprising a normalization module adapted to normalize the secondary filter parameters to the primary filter parameters.

3. The system of claim 1, further comprising a mapping module adapted to map the secondary filter parameters to the primary source parameters based on linguistic similarities between target sounds in the secondary language and primary source parameters in the primary language.

4. The system of claim 1, further comprising:

an input receptive of text; and

a speech synthesizer adapted to convert the text-to-speech based on said primary filter parameters and said secondary filter parameters.

5. The system of claim 1, further comprising an input receptive of an initial set of secondary filter parameters.

6. The system of claim 5, further comprising a similarity assessment module adapted to assess similarity between the initial set of secondary filter parameters and said primary filter parameters.

7. The system of claim 6, further comprising a memory management module adapted to compare similarity of the initial set of secondary filter parameters to a similarity threshold, to select a portion of the secondary filter parameters based on the comparison, to store the portion of the secondary filter parameters that are selected in a memory resource, and to discard an unselected portion of the initial set of secondary filter parameters.

8. The system of claim 7, wherein the similarity threshold is selected to ensure that the secondary filter parameters of the initial set that are related to sounds not present in the primary language are not discarded.

9. The system of claim 7, wherein said memory management module is adapted to monitor use of the memory resource and to dynamically adjust the similarity threshold based on scarcity of the memory resource.

10. The system of claim 1, wherein said secondary filter parameters are selected based on at least one of their relationships to sounds not present in the primary language and their dissimilarities to said primary filter parameters.

11. The system of claim 1, further comprising:

a similarity assessment module adapted to assess linguistic similarity between target sounds in the secondary language and primary source parameters in the primary language;

a memory management module adapted to compare the linguistic similarities to a linguistic similarity threshold, store secondary source parameters providing information mainly about a speaker in the second language in memory based on linguistic similarity between the secondary source parameters and target sounds exhibiting linguistic similarities falling below the predetermined threshold; and

a mapping module adapted to map secondary filter parameters providing information mainly about the target sounds exhibiting linguistic similarities falling below the predetermined threshold to the secondary source parameters based on linguistic similarity.

12. The system of claim 1, further comprising a plurality of primary prosody parameters, wherein at least one secondary filter parameter is mapped to a primary prosody parameter.

13. The system of claim 12, further comprising a plurality of secondary prosody parameters selected to supplement said primary prosody parameters, wherein at least one secondary filter parameter is mapped to a secondary prosody parameter.

14. The system of claim 1, further comprising:

a parameter output adapted to transmit an amount of available local memory and information relating to linguistic parameters stored in local memory to a supply of additional linguistic parameters not stored in local memory; and

a parameter input receptive of additional linguistic parameters preselected based on the amount of available local memory, including additional filter parameters pre-mapped to said primary source parameters.

15. The system of claim 14, wherein the additional filter parameters are pre-normalized to said primary filter parameters.

16. The system of claim 14, wherein the additional filter parameters are pre-mapped to primary prosody parameters stored in local memory.

17. The system of claim 16, wherein the additional linguistic parameters include additional prosody parameters pre-selected to supplement the primary prosody parameters based on the amount of available local memory.

18. The system of claim 14, wherein said parameter output is adapted to transmit a user-specified quality preference, and the additional linguistic parameters are preselected based on the user-specified quality preference.

19. A method of operation for use with a multilingual text-to-speech system, comprising:

accessing primary source parameters providing information mainly about a speaker of a primary language;

accessing primary filter parameters providing information mainly about sounds in the primary language; and

accessing secondary filter parameters providing information mainly about sounds in a secondary language, wherein at least one secondary filter parameter is normalized to the primary filter parameters and mapped to a primary source parameter.

20. The method of claim 19, further comprising normalizing the secondary filter parameters to the primary filter parameters.

21. The method of claim 19, further comprising mapping the primary source parameters to the secondary filter parameters based on linguistic similarities between target sounds in the secondary language and primary source parameters in the primary language.

22. The method of claim 19, further comprising:

receiving text; and

converting the text-to-speech based on the primary filter parameters and the secondary filter parameters.

23. The method of claim 19, further comprising receiving an initial set of secondary filter parameters.

24. The method of claim 19, further comprising assessing similarity between the initial set of secondary filter parameters and the primary filter parameters.

25. The method of claim 24, further comprising:

comparing similarity of the initial set of secondary filter parameters to a similarity threshold;

selecting a portion of the secondary filter parameters based on the comparison;

storing the portion of the secondary filter parameters that are selected in a memory resource; and

discarding an unselected portion of the initial set of secondary filter parameters.

26. The method of claim 25, further comprising selecting the similarity threshold to ensure that the secondary filter parameters of the initial set that are related to sounds not present in the primary language are not discarded.

27. The method of claim 25, further comprising:

monitoring use of the memory resource; and

dynamically adjusting the similarity threshold based on scarcity of the memory resource.

28. The method of claim 19, further comprising selecting the secondary filter parameters based on at least one of their relationships to sounds not present in the primary language and their dissimilarities to the primary filter parameters.

29. The method of claim 19, further comprising:

assessing linguistic similarity between target sounds in the secondary language and primary source parameters in the primary language;

comparing the linguistic similarities to a linguistic similarity threshold;

storing secondary source parameters providing information mainly about a speaker in the second language in memory based on linguistic similarity between the secondary source parameters and target sounds exhibiting linguistic similarities falling below the predetermined threshold; and

mapping secondary filter parameters providing information mainly about the target sounds exhibiting linguistic similarities falling below the predetermined threshold to the secondary source parameters based on linguistic similarity.

30. The method of claim 19, further comprising:

accessing a plurality of primary prosody parameters; and

mapping at least one secondary filter parameter to the primary prosody parameters.

31. The method of claim 30, further comprising:

accessing a plurality of secondary prosody parameters selected to supplement said primary prosody parameters; and

mapping at least one secondary filter parameters to said secondary prosody parameters.

32. The method of claim 0.19, further comprising:

transmitting an amount of available local memory and information relating to linguistic parameters stored in local memory to a supply of additional linguistic parameters not stored in local memory; and

receiving additional linguistic parameters preselected based on the amount of available local memory, including additional filter parameters pre-mapped to said primary source parameters.

33. The method of claim 32, wherein the additional filter parameters are pre-normalized to said primary filter parameters.

34. The method of claim 32, wherein the additional filter parameters are pre-mapped to primary prosody parameters stored in local memory.

35. The method of claim 34, wherein the additional linguistic parameters include additional prosody parameters pre-selected to supplement the primary prosody parameters based on the amount of available local memory.

36. The system of claim 32, further comprising transmitting a user-specified quality preference, wherein the additional linguistic parameters are further preselected based on the user-specified quality preference.

37. A method of operation for use with a service adapted to provide linguistic parameters to a multilingual text-to-speech apparatus, comprising:

receiving a request for additional linguistic parameters;

identifying an additional language based on the request; and

transmitting additional linguistic parameters, including additional filter parameters providing information mainly about sounds in the additional language.

38. The method of claim 37, further comprising transmitting an additional synthesizer front end operable to adapt a preexisting speech synthesizer to employ the additional filter parameters.

39. The method of claim 37, further comprising:

identifying an amount of available memory based on the request; and

pre-selecting the additional linguistic parameters based on the amount of available memory.

40. The method of claim 37, further comprising:

identifying a user-specified quality preference based on the request; and

pre-selecting the additional linguistic parameters based on the user-specified quality preference.

41. The method of claim 37, further comprising:

identifying preexisting linguistic parameters based on the request; and

pre-selecting additional linguistic parameters based on need to supplement the preexisting linguistic parameters, including at least one of additional filter parameters, additional source parameters, and additional prosody parameters.

42. The method of claim 37, further comprising:

identifying preexisting linguistic parameters based on the request; and

pre-processing the additional linguistic parameters to merge the additional linguistic parameters with the pre-existing linguistic parameters.

43. The method of claim 42, further comprising pre-mapping the additional filter parameters to preexisting source parameters of the preexisting linguistic parameters.

44. The method of claim 42, further comprising pre-normalizing the additional filter parameters to preexisting filter parameters of the preexisting linguistic parameters.

45. The method of claim 42, further comprising pre-mapping at least one additional filter parameter to preexisting prosody parameters of the preexisting linguistic parameters.