Methods employing phase state analysis for use in speech synthesis and recognition

1. A computer-implemented method for analyzing, predicting, and/or modifying acoustic units of prosodic human speech utterances for use in speech synthesis or speech recognition, the method comprising:

(a) initiating analysis of acoustic wave data representing the human speech utterances, via the phase state of the acoustic wave data, the acoustic wave data being in constrained or unconstrained form;

(b) using one or more phase state defined acoustic wave metrics as common elements for analyzing, and optionally modifying, one or more measurable acoustic parameters selected from the group consisting of pitch, amplitude, duration, and other measurable acoustic parameters of the acoustic wave data, at predetermined time intervals, two or more of the acoustic parameters optionally being analyzed and/or modified simultaneously;

(c) analyzing acoustic wave data representing a selected one of the acoustic units to determine the phase state of the acoustic unit; and

(d) analyzing the acoustic wave data representing the selected acoustic unit to determine at least one acoustic parameter of the acoustic unit with reference to the determined phase state of the selected acoustic unit.

2. A method according to claim 1 comprising concatenating the selected acoustic unit with an additional acoustic unit having at least one acoustic parameter compatible with the respective selected acoustic unit parameter as determined in a phase state of the additional acoustic unit similar to, or identical with, the phase state of the selected acoustic unit.

3. A method according to claim 1 comprising concatenating the selected acoustic unit with an additional acoustic unit having a pitch, amplitude and duration compatible with the pitch, amplitude and duration of the selected acoustic unit, as determined in a phase state of the additional acoustic unit similar to, or identical with, the phase state of the selected acoustic unit.

4. A method according to claim 1 comprising matching a sequence of the acoustic units with a sequence of text capable of visually representing the speech utterances.

5. A method according to claim 4 wherein the speech utterances have an identifiable prosody and the method comprises labeling the text with prosodic phonetic units to represent the sequence of text with the prosody identified in the speech signal.

6. A method according to claim 5 comprising tagging each prosodic phonetic unit with a bundle of acoustic feature values to describe the prosodic phonetic unit acoustically.

7. A method according to claim 6 wherein the acoustic feature values comprise values for context-independent prosodic phonetic unit features and, optionally, context-dependent prosodic phonetic unit features determined by applying linguistic rules to the sequence of text.

8. A method according to claim 1 comprising assembling the sequence of acoustic units from available acoustic units in a database of acoustic units, and wherein, optionally, each available acoustic unit in the database comprises a recorded element of speech voiced by a human speaker.

9. A method according to claim 1 comprising determining a desired acoustic unit pathway comprising a sequence of acoustic feature vectors corresponding with a sequence of the acoustic units or with a sequence of text representing the speech utterances.

10. A method according to claim 9 wherein the acoustic feature vectors each comprise a bundle of feature values selected for closeness to a statistical mean of the values of candidate acoustic units to be matched with a prosodic phonetic unit or one of the prosodic phonetic units and, optionally, for acoustic continuity with at least one adjacent acoustic feature vector.

11. A method according to claim 1 comprising modifying a candidate acoustic unit by analyzing the candidate acoustic unit wave data into a vocal tract resonance signal and a residual glottal signal, modifying an acoustic parameter of the glottal signal and recombining the vocal tract resonance signal with the modified glottal signal to provide a modified candidate acoustic unit.

12. A method according to claim 11 comprising analyzing the glottal signal to determine the time-dependent amplitude of the glottal signal with reference to the phase state of the glottal signal, determining the fundamental frequency of the glottal signal in the phase state and modifying the fundamental frequency of the glottal signal in the phase state to have a desired value.

13. A method according to claim 11 wherein the vocal tract resonance signal comprises partial correlation coefficients and the method comprises modifying the vocal tract resonance signal by converting the partial correlation coefficients to log area ratios and altering or interpolating the log area ratios.

14. A method according to claim 1 wherein the acoustic metrics or acoustic parameters comprise one or more metrics or parameters selected from the group consisting of pitch, amplitude, duration, fundamental frequency, formants, mel-frequency cepstral coefficients, energy, and time.

15. A method according to claim 1 wherein the speech signal is a synthesized speech signal comprising a sequence of acoustic units concatenated to audibilize the sequence of text.

16. A method according to claim 1 wherein the acoustic units are derived from prosodic speech recordings generated by human speakers pronouncing text annotated according to specific rules for a defined prosody.

17. A method according to claim 1 wherein the sequence of text is generated to visually represent the speech recognized in the speech signal.

18. A method according to claim 1 wherein the sequence of text is selected from the group consisting of a phrase, a sentence, multiple sentences, a paragraph, multiple paragraphs, a discourse, and a written work.

19. A computerized system comprising software for performing a method according to claim 1 , the software being stored in, or resident in, computer readable media.