USING FINITE STATE GRAMMARS TO VARY OUTPUT GENERATED BY A TEXT-TO-SPEECH SYSTEM

• US 20080312929A1
• Filed: 06/12/2007
• Published: 12/18/2008
• Est. Priority Date: 06/12/2007
• Status: Abandoned Application

• Current Assignee: Nuance Communications, Inc. (Microsoft Corporation)
• Original Assignee: International Business Machines Corporation
• Inventors: VILA, ROBERTO, BLASS, OSCAR J., PATEL, PARITOSH D., RUBACK, HARVEY M.
• Application Number:
  US11/761,852
• Publication Number:
  US 20080312929A1
• Time in Patent Office: Days
• US Class Current: 704/260
• 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

Abstract

The present invention discloses a text-to-speech system that provides output variability. The system can include a finite state grammar, a variability engine and a text-to-speech engine. The finite state grammar can contain a phrase role consisting of one or more phrase elements. The phrase rule can deterministically generate a variable text phrase based upon at least one random number. The phrase rule can include a definition for each of the phrase elements. Each definition can be associated with at least one defined text string. The variability engine can construct a random text phrase responsive to receiving an action command, wherein said finite state grammar is used to create the text phrase. The variability engine can also rely on user-specified weights to adjust the output probabilities. The speech-to-text engine can convert the text phrase generated by the variability engine into speech output.

Claims

1. A method for using a finite state grammar to vary output of a text-to-speech system comprising:

a text-to-speech system receiving an action command;

accessing a finite state grammar that corresponds to the received action command;

constructing a text phrase based on the finite state grammar; and

synthesizing the constructed text phrase into speech output.

2. The method of claim 1, wherein the constructing step further comprises:

generating a numeric value;

mapping the generated numeric value to a text string for a phrase element of the finite state grammar;

selecting the corresponding text string for use in the text phrase;

determining an existence of weighting data for the phrase element, wherein the weighting data represents a set of predefined selection preferences that correspond to the text strings associated with the phrase element; and

when weighting data exists, applying the weighting data to the phrase element.

3. The method of claim 2, wherein the applying step further comprises:

comparing the generated numeric value against the set of predefined selection preferences, wherein the set of selection preferences contains one or more weighted values;

determining which weighted value corresponds to the generated numeric value;

ascertaining an equivalency between the text string associated with the weighted value and the previously selected text string; and

when the result of the ascertaining step indicates inequality, replacing the previously selected text string with the text string associated with the weighted value.

4. The method of claim 3, wherein the weighted value is one of a numeric value and a range of numeric values.

5. The method of claim 2, wherein the generating step utilizes an algorithm to produce a pseudo-random number.

6. The method of claim 2, wherein the steps of claim 2 are repeated for each phrase element defined within the finite state, grammar.

7. The method of claim 1, wherein the finite state grammar defines a phrase rule for the text phrase, wherein the phrase rule describes an order for linking one or more phrase elements, and wherein the finite state grammar defines a set of acceptable text strings for each phrase element.

8. The method of claim 1, wherein the accessing and constructing steps of claim 1 are performed by a variability engine component of the text-to-speech system, wherein the variability engine utilizes the finite state grammar to vary one or more phrase elements of the text phrase, whereby producing a larger variety of speech output for a single action command.

9. The method of claim 1, wherein said steps of claim 1 are performed by at least one machine in accordance with at least one computer program stored in a computer readable media, said computer programming having a plurality of code sections that are executable by the at least one machine.

10. A text-to-speech system that provides output variability comprising:

a finite state grammar comprising a phrase rule consisting of one or more phrase elements, wherein the phrase rule deterministically generates a variable text phrase upon receiving at least one random number and an action command, the finite state grammar can also comprise a plurality of definitions, one for each phrase element, wherein each definition is associated with at least one text string, wherein the variable text phrase is generated by concatenating a plurality of the text strings together in accordance with the phrase rule;

a variability engine configured to construct a random text phrase responsive to receiving an action command, wherein said finite state grammar is used to create the text phrase; and

a speech-to-text engine configured to convert the text phrase generated by the variability engine into speech output.

11. The system of claim 10, wherein the variability engine further comprises:

a number generator configured to generate a numeric value, wherein the generated numeric value corresponds to one of the text strings defined for the phrase element; and

a weight applicator configured to adjust a selection of the text string based upon weighting data.

12. The system of claim 11, wherein die weighting data contains a weight value for each text string of the phrase element definition, and wherein the weight value is one of a numeric value and a range of numeric values.

13. The system of claim 11, wherein the number generator is one of a pseudo-random number generating algorithm, a quasi-random number generating algorithm, and a physical random number generator.

14. A speech synthesis method comprising:

receiving a command for generating speech;

determining one of a plurality of finite state grammars that is associated with the received command, wherein the finite state grammar comprises a plurality of phrase elements, each element corresponding to a plurality of different text strings;

randomly generating at least one number, which is used to select one of the different text strings for each of the phrase elements;

concatenating the selected text strings in an order determined by the finite grammar; and

text-to-speech converting the concatenated text strings to produce synthesized speech output.

15. The method of claim 14, wherein the at least one randomly generated number is a plurality of randomly generated numbers, each randomly generated number corresponding to one of the phrase elements.

16. The method of claim 14, further comprising:

associating at least one weight to at least one of the text strings, wherein the associated weight causes one of the text strings of a phrase element to be selected more often than another of the text strings of the phrase element.

17. The method of claim 16, wherein the receiving, determining, generating, concatenating, and converting steps are automatically performed by a machine in accordance with a set of programmatic instructions stored in a machine readable medium.

18. The method of claim 17, wherein the set of programmatic instructions are part of a text-to-speech engine used by a turn-based speech processing system.

19. The method of claim 17, wherein the set of programmatic instructions are part of a text-to-speech engine residing within a stand-alone computing device having speech generation capabilities, said method being performed by tire computing device.