IP Library Granted Patent US 8,321,222
Granted Patent B2
US 8,321,222 · App. 11/838,609 · Granted Nov 27, 2012

Synthesis by generation and concatenation of multi-form segments

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Quick Facts
Patent No.
US 8,321,222
App. No.
11/838,609
Granted
Nov 27, 2012
Kind
B2
Abstract

A speech synthesis system and method is described. A speech segment database references speech segments having various different speech representational structures. A speech segment selector selects from the speech segment database a sequence of speech segment candidates corresponding to a target text. A speech segment sequencer generates from the speech segment candidates sequenced speech segments corresponding to the target text. A speech segment synthesizer combines the selected sequenced speech segments to produce a synthesized speech signal output corresponding to the target text.

Claims (51)

1. A speech synthesis system implemented using at least one hardware implemented processor, the system comprising:

a speech segment database referencing speech segments having a plurality of different types of speech representational structures including:

i. statistical state model based speech signals, and

ii. template based speech signals;

a speech segment selector for selecting from the speech segment database a sequence of statistical state model based and template based speech segment candidates corresponding to a target text;

a speech segment sequencer for generating from the speech segment candidates sequenced statistical state model based and template based speech segments corresponding to the target text; and

a speech segment synthesizer for combining the sequenced statistical state model based and template based speech segments to produce a synthesized speech signal output corresponding to the target text.

2. A speech synthesis system according to claim 1 , wherein the different types of speech representational structures include statistical state model-based speech signals augmented with template information.

3. A speech synthesis system according to claim 1 , wherein the speech segment selector uses a statistical state model for selecting the speech segment candidates.

4. A speech synthesis system according to claim 3 , wherein the speech segment selector uses template information to augment the statistical state model.

5. A speech synthesis system according to claim 1 , wherein the different types of speech representational structures share at least one parameter component.

6. A speech synthesis system according to claim 5 , wherein the shared parameter component is encoded differently in different speech representational structures.

7. A speech synthesis system according to claim 1 , wherein the speech segment sequencer uses static observations in generating the sequenced speech segments.

8. A speech synthesis system according to claim 1 , wherein the speech segment sequencer uses observations from the speech segment selector in generating the sequenced speech segments.

9. A speech synthesis system according to claim 1 , wherein the speech segment sequencer uses static observations and observations from the speech segment selector in generating the sequenced speech segments.

10. A speech synthesis system according to claim 1 , wherein the speech segment selector uses statistically derived cost-functions for selecting the speech segment candidates.

11. A speech synthesis system according to claim 1 , wherein the speech segment sequencer uses statistically derived cost-functions for generating the sequenced speech segments.

12. A speech synthesis system according to claim 1 , wherein the speech segment selector uses empirical rules for selecting the speech segment candidates.

13. A speech synthesis system according to claim 1 , wherein the speech segment sequencer uses empirical rules for generating the sequenced speech segments.

14. A speech synthesis system according to claim 1 , wherein the speech segment selector uses psycho-acoustic rules for selecting the speech segment candidates.

15. A speech synthesis system according to claim 1 , wherein the speech segment sequencer uses psycho-acoustic rules for generating the sequenced speech segments.

16. A speech synthesis system according to claim 10 , wherein the statistically derived cost-functions are based on sequences of speech segment observations.

17. A speech synthesis system according to claim 16 , wherein the sequences of speech segment observations are described by a Markov process.

18. A speech synthesis system according to claim 11 , wherein the statistically derived cost-functions are based on sequences of speech segment observations.

19. A speech synthesis system according to claim 18 , wherein the sequences of speech segment observations are described by a Markov process.

20. A method of speech synthesis comprising:

with a system implemented using at least one hardware implemented processor:

referencing in a speech segment database speech segments having a plurality of different types of speech representational structures including:

i. statistical state model based speech signals, and

ii. template based speech signals;

selecting from the speech segment database a sequence of statistical state model based and template based speech segment candidates corresponding to a target text;

generating from the speech segment candidates sequenced statistical state model based and template based speech segments corresponding to the target text; and

combining the sequenced statistical state model based and template based speech segments to produce a synthesized speech signal output corresponding to the target text.

21. A method according to claim 20 , wherein the different types of speech representational structures include statistical state model-based speech signals augmented with template information.

22. A method according to claim 20 , wherein a statistical state speech model is used in selecting the sequence of speech segment candidates.

23. A method according to claim 22 , wherein the statistical state speech model is augmented by template information.

24. A method according to claim 20 , wherein the different types of speech representational structures share at least one parameter component.

25. A method according to claim 24 , wherein the shared parameter component is encoded differently in different speech representational structures.

26. A method according to claim 20 , wherein static observations are used in generating the sequenced speech segments.

27. A method according to claim 20 , wherein observations from the selecting the sequence of speech segment candidates are used in the generating the sequenced speech segments.

28. A method according to claim 20 , wherein static observations and observations from the selecting the sequence of speech segment candidates are used in the generating the sequenced speech segments.

29. A method according to claim 20 , wherein statistically derived cost-functions are used for selecting the speech segment candidates.

30. A method according to claim 20 , wherein statistically derived cost-functions are used for generating the sequenced speech segments.

31. A method according to claim 20 , wherein empirical rules are used for selecting the speech segment candidates.

32. A method according to claim 20 , wherein empirical rules are used for generating the sequenced speech segments.

33. A method according to claim 20 , wherein psycho-acoustic rules are used for selecting the speech segment candidates.

34. A method according to claim 20 , wherein psycho-acoustic rules are used for generating the sequenced speech segments.

35. A method according to claim 29 , wherein the statistically derived cost-functions are based on sequences of speech segment observations.

36. A method according to claim 35 , wherein the sequences of speech segment observations are described by a Markov process.

37. A method according to claim 30 , wherein the statistically derived cost-functions are based on sequences of speech segment observations.

38. A method according to claim 37 , wherein the sequences of speech segment observations are described by a Markov process.

Assignments (6)
RELEASE (REEL 067417 / FRAME 0303) Recorded Jan 2, 2025
From: WELLS FARGO BANK, NATIONAL ASSOCIATION
To: CERENCE OPERATING COMPANY
Reel/Frame 069797/0422 →
SECURITY AGREEMENT Recorded Apr 15, 2024
From: CERENCE OPERATING COMPANY
To: WELLS FARGO BANK, N.A., AS COLLATERAL AGENT
Reel/Frame 067417/0303 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 28, 2023
From: NUANCE COMMUNICATIONS, INC.
To: CERENCE OPERATING COMPANY
Reel/Frame 064723/0519 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 15, 2021
From: NUANCE COMMUNICATIONS, INC.
To: CERENCE OPERATING COMPANY
Reel/Frame 055927/0620 →
CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNEE'S ADDRESS FROM BOSTON TO BURLINGTON PREVIOUSLY RECORDED ON REEL 019741 FRAME 0959. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNEE'S ADDRESS FROM BOSTON TO BURLINGTON. Recorded Aug 28, 2007
From: POLLET, VINCENT; BREEN, ANDREW
To: NUANCE COMMUNICATIONS, INC.
Reel/Frame 019752/0342 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 24, 2007
From: POLLET, VINCENT; BREEN, ANDREW
To: NUANCE COMMUNICATIONS, INC.
Reel/Frame 019741/0959 →