PRE-SAVED DATA COMPRESSION FOR TTS CONCATENATION COST

• US 20110246200A1
• Filed: 04/05/2010
• Published: 10/06/2011
• Est. Priority Date: 04/05/2010
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Zhang, Guoliang, Weng, Zhiwei, Song, Huicheng
• Granted Patent: US 8,798,998 B2
• Time in Patent Office: Days
• US Class Current: 704/260
• CPC Class Codes: G10L 13/07 Concatenation rules

Abstract

Pre-saved concatenation cost data is compressed through speech segment grouping. Speech segments are assigned to a predefined number of groups based on their concatenation cost values with other speech segments. A representative segment is selected for each group. The concatenation cost between two segments in different groups may then be approximated by that between the representative segments of their respective groups, thereby reducing an amount of concatenation cost data to be pre-saved.

Claims

1. A method to be executed at least in part in a computing device for performing concatenative speech synthesis, the method comprising:

determining feature vectors for speech segments based on a matrix of concatenation costs;

applying distance weighting to each speech segment pair based on the feature vectors;

clustering the speech segments into a predefined number of groups such that an average distance between speech segments within each group is minimized;

selecting a representative speech segment for each group; and

generating a compressed concatenation cost matrix based on the representative speech segments.

2. The method of claim 1, further comprising:

pre-saving the compressed concatenation cost matrix for real time computations in synthesizing speech.

3. The method of claim 1, wherein the distance weighting is applied employing one of:

a Euclidean distance function and a city block distance function.

4. The method of claim 1, wherein the matrix of concatenation costs is constructed along a preceding speech segments axis and a following speech segments axis.

5. The method of claim 4, wherein a concatenation cost between a preceding speech segment and a following speech segment is different from a concatenation cost between the same speech segments with an order of the speech segments reversed.

6. The method of claim 1, wherein the representative speech segment for each group is selected such that an average distance between the representative speech segment and other speech segments within the same group is minimized.

7. The method of claim 1, wherein a number of the groups is determined based on at least one from a set of:

a total number of speech segments, distances between the speech segments, and a desired reduction in concatenation cost data.

8. The method of claim 1, wherein the representative speech segment for each group is selected based on one of a median concatenation cost and a mean concatenation cost of each group.

9. The method of claim 1, wherein the speech segments include one of:

individual phones, diphones, half-phones, and syllables.

10. A text to speech (TTS) synthesis system for generating speech employing compressed concatenation cost data, the system comprising:

a speech segment data store;

an analysis engine; and

a speech synthesis engine configured to;

determine a feature vector for each speech segment that comprises concatenation cost values of each speech segment with other speech segments;

apply distance weighting to each speech segment pair based on their respective feature vectors;

cluster the speech segments into a predefined number of groups such that an average distance between speech segments within each group is minimized;

select a representative speech segment for each group such that an average distance between the representative speech segment and other speech segments within the same group is minimized;

generate a compressed concatenation cost matrix based on the representative speech segments; and

pre-save the compressed concatenation cost matrix for real time computations in synthesizing speech.

11. The TTS system of claim 10, wherein the distance weighting is applied such that a sensitivity to compression errors is reduced.

12. The TTS system of claim 10, wherein the representative speech segment for each group is further selected based on center re-estimation.

13. The TTS system of claim 12, wherein the center re-estimation includes estimating a concatenation cost value based on a portion of whole samples such that a computation cost is reduced when speech segment numbers are relatively large.

14. The TTS system of claim 10, wherein the speech segment data store is configured to receive speech segments from at least one of:

a user input and a set of pre-recorded speech patterns.

15. The TTS system of claim 10, wherein the analysis engine is configured to:

perform at least one from a set of;

text analysis, prosody analysis, and phonetic analysis; and

provide input to the speech synthesis engine for segment selection based on the performed analyses.

16. A computer-readable storage medium with instructions stored thereon for generating speech employing compressed concatenation cost data, the instructions comprising:

determining feature vectors for speech segments based on a matrix of concatenation costs constructed along a preceding speech segments axis and a following speech segments axis;

applying distance weighting to each speech segment pair based on their respective feature vectors;

clustering the speech segments into M preceding segment and N following segment groups such that an average distance between speech segments within each group is minimized;

selecting a representative speech segment for each group;

generating a compressed concatenation cost matrix such that a concatenation cost between two speech segments is approximated by a concatenation cost between representative segments of respective preceding speech segment and following speech segment groups; and

pre-saving the compressed concatenation cost matrix for real time computations in synthesizing speech.

17. The computer-readable medium of claim 16, wherein the distance weighting is applied employing distance function:

Σ

_m=1ⁿ{abs(cc_i,m−

cc_j,m)*[K₀−

(cc_i,m+cc_j,m)]}², where cc_i,j are concatenation costs between speech segments i and j, and K₀ is a predefined constant.

18. The computer-readable medium of claim 16, wherein the representative speech segment for each group is selected based on one of:

minimization of an average distance between the representative speech segment and other speech segments within the same group, median concatenation cost of the group, and a mean concatenation cost of the group.

19. The computer-readable medium of claim 16, wherein the instructions further comprise:

determining M and N based on at least one from a set of;

the total number of speech segments, distances between the speech segments, and a desired reduction in concatenation cost data

20. The computer-readable medium of claim 16, wherein a size of pre-saved concatenation data is reduced by [n²/(M×

N)], where n is the total number of the speech segments.