Method for forming the excitation signal for a glottal pulse model based parametric speech synthesis system

• US 10,621,969 B2
• Filed: 02/11/2019
• Issued: 04/14/2020
• Est. Priority Date: 05/28/2014
• Status: Active Grant

• Current Assignee: Genesys Telecommunications Laboratories Incorporated (Genesys Cloud Services Incorporated)
• Original Assignee: Genesys Telecommunications Laboratories Incorporated (Genesys Cloud Services Incorporated)
• Inventors: Dachiraju, Rajesh, Raghavendra, E. Veera, Ganapathiraju, Aravind
• Primary Examiner(s): Dorvil, Richemond
• Assistant Examiner(s): Chavez, Rodrigo A
• Application Number:
  US16/272,130
• Publication Number:
  US 20190172442A1
• Time in Patent Office: 428 Days
• Field of Search: 704 7, 704 10, 704201, 704208, 704210, 704215, 704224, 704234, 704248
• CPC Class Codes: G10L 13/02 Methods for producing synthetic speech; Speech synthesisers
• CPC Class Codes: G10L 13/027 Concept to speech synthesisers; Generation of natural phrases from machine-based concepts generation of parameters for speech synthesis out of text G10L13/08
• CPC Class Codes: G10L 13/06 Elementary speech units used in speech synthesisers; Concatenation rules

Abstract

A system and method are presented for forming the excitation signal for a glottal pulse model based parametric speech synthesis system. The excitation signal may be formed by using a plurality of sub-band templates instead of a single one. The plurality of sub-band templates may be combined to form the excitation signal wherein the proportion in which the templates are added is dynamically based on determined energy coefficients. These coefficients vary from frame to frame and are learned, along with the spectral parameters, during feature training. The coefficients are appended to the feature vector, which comprises spectral parameters and is modeled using HMMs, and the excitation signal is determined.

Claims

1. A method performed by a processing circuit for identification of sub-band Eigen pulses from a glottal pulse database for training a speech synthesis system, wherein the method comprises:

a. receiving pulses from the glottal pulse database;

b. decomposing each pulse into a plurality of sub-band components;

c. distributing the plurality of sub-band components into a plurality of databases based on a frequency level of sub-band component of the plurality of sub-band components, wherein each database of the plurality of databases corresponds to a frequency level of a sub-band component of the plurality of sub-band components;

d. determining a vector representation of each database wherein the determining a vector representation of each database further comprises a set of distances from a set of fixed number of points of a metric space, obtained as centroids after a metric based clustering of a large set of signals from the metric space;

e. determining Eigen pulse values, from the vector representation, for each database;

f. selecting a best Eigen pulse for each database for use in synthesis; and

g. applying the selected Eigen pulse from the speech signal to form an excitation signal, wherein the excitation signal is applied in the speech synthesis system to synthesize speech.

2. The method of claim 1, wherein the plurality of sub-band components comprises a low band and a high band.

3. The method of claim 1, wherein the glottal pulse database is created by:

a. performing linear prediction analysis on a speech signal;

b. performing inverse filtering of the signal to obtain an integrated linear prediction residual; and

c. segmenting the integrated linear prediction residual into glottal cycles to obtain a number of glottal pulses.

4. The method of claim 1, wherein the decomposing further comprises:

a. determining a cut off frequency;

wherein said cut off frequency separates the sub-band components into groupings;

b. obtaining a zero crossing at the edge of the low frequency bulge;

c. placing zeros in the high band region of the spectrum prior to obtaining the time domain version of the low frequency component of glottal pulse, wherein the obtaining comprises performing inverse FFT; and

d. placing zeros in the lower band region of the spectrum prior to obtaining the time domain version of the high frequency component of the glottal pulse, wherein the obtaining comprises performing inverse FFT.

5. The method of claim 4, wherein the groupings comprise a lower band grouping and higher band grouping.

6. The method of claim 4, wherein the separating of sub-band components into groupings is performed using a ZFR method and applied on the spectral magnitude.