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Speech Processing 15-492/18-492 Speech Synthesis Signal Processing Signal Manipulation Signal Parameterization Signal Parameterization Joining Joining LPC LPC PSOLA: pitch and duration modification PSOLA: pitch


  1. Speech Processing 15-492/18-492 Speech Synthesis Signal Processing

  2. Signal Manipulation Signal Parameterization � Signal Parameterization � � Joining Joining � � LPC LPC � � PSOLA: pitch and duration modification PSOLA: pitch and duration modification � Statistical Parameterization � Statistical Parameterization � � MELCEP/MLSA MELCEP/MLSA � � LSF, STRAIGHT, HNM, HSM LSF, STRAIGHT, HNM, HSM �

  3. TTS Signal Processing � Join together pieces of speech Join together pieces of speech � � Prosodic modification Prosodic modification � � Pitch (F0) Pitch (F0) � � Duration Duration � � Power Power � � Change spectral properties Change spectral properties � � Stress/ Stress/unstress unstress � � Spectral tilt Spectral tilt � � Speaking style Speaking style �

  4. Joining Just put them together � Just put them together � � Gets clicks at join points Gets clicks at join points � Join them at zero crossings � Join them at zero crossings � Window them and overlap them � Window them and overlap them � � WSOLA WSOLA � Join them at pitch periods � Join them at pitch periods �

  5. Prosodic Modification independently Modify pitch and duration independently � Modify pitch and duration � Changing sample rate changes both � Changing sample rate changes both � � “chipmunk” style speech “chipmunk” style speech � Duration � Duration � � Duplicate/delete parts of the signal Duplicate/delete parts of the signal � Pitch � Pitch � � “resample” to change pitch “resample” to change pitch �

  6. Speech and Short Term Signals

  7. Duration Modification

  8. Pitch Modification

  9. Modify pitch and duration Find ideal pitch periods and duration � Find ideal pitch periods and duration � Find closest actual periods from units � Find closest actual periods from units � End with � End with � � Pitch period (short term signals) Pitch period (short term signals) � � Distances between them Distances between them �

  10. Signal Reconstruction � TD TD- -PSOLA™ PSOLA™ � � Time domain pitch synchronous overlap and add Time domain pitch synchronous overlap and add � � Patented by France Telecom Patented by France Telecom � � Expired 2004 Expired 2004 � � Very efficient: Very efficient: � � No FFT (or inverse FFT) No FFT (or inverse FFT) � � Can modify Hz * 2.0 (or 0.5) Can modify Hz * 2.0 (or 0.5) � � The reason no one publishes algorithms The reason no one publishes algorithms � � The (partial) reason unit selection typically doesn’t The (partial) reason unit selection typically doesn’t � do pitch/duration modification do pitch/duration modification

  11. LPC: Linear predictive coding • Linear predictive coding – Predict next sample point from previous – Weighted sum of previous points – Filter of order p. – Residual excited LPC

  12. LPC � Works well but can be Works well but can be buzzy buzzy � � Can be very compact Can be very compact � � Can be pitch synchronous Can be pitch synchronous � � Excited Excited � � Pulse Pulse � � Triangular pulse Triangular pulse � � Multi Multi- -pulse pulse � � Full residual Full residual � � Used in standard speech coding Used in standard speech coding � � LPC10: 2.4kps LPC10: 2.4kps � � CELP: codebook excited LPC CELP: codebook excited LPC �

  13. Other Parametric Representations � Typically split spectral and residual Typically split spectral and residual � � MBROLA: MBROLA: � � Multi Multi- -band overlap and add band overlap and add � � HNM/HSM: HNM/HSM: � � Harmonic plus (noise/stochastic) modeling Harmonic plus (noise/stochastic) modeling � � STRAIGHT STRAIGHT � � MELCEP/MLSA MELCEP/MLSA � � Often used in HMM synthesis Often used in HMM synthesis � � Sinusoidal (HARMONIC) Sinusoidal (HARMONIC) � � Wavelet Wavelet � � LSF/LPC LSF/LPC �

  14. Choosing the right unit type Diphones � Diphones � � Phone Phone- -phone phone � � Joins at stable portions, not transitions Joins at stable portions, not transitions � Half phone (AT&T Natural Voices) � Half phone (AT&T Natural Voices) � Hybrid systems (Hadifix Hadifix – – Bonn systems) Bonn systems) � Hybrid systems ( � Other selection systems: � Other selection systems: � � Syllable, phone, HMM state Syllable, phone, HMM state � � Even frame level Even frame level �

  15. Acoustically Derived Units E.g Bacchiani Bacchiani 99 or Rita Singh CMU 99 or Rita Singh CMU � E.g � From some waveforms � From some waveforms � � Find N most diverse unit types Find N most diverse unit types � � Varied in length Varied in length � Still need to map letters to units � Still need to map letters to units �

  16. Acoustic Phonetic Clustering � Parameterize database Parameterize database � � Melcep Melcep plus power plus power � � K K- -means means � � Euclidean distance measure Euclidean distance measure � � 100 clusters 100 clusters � � Label DB with best cluster Label DB with best cluster � � Build Build clunits clunits synthesizer synthesizer � � Can’t predict APC cluster directly Can’t predict APC cluster directly � � Use held out data for testing Use held out data for testing �

  17. Acoustic Phonetic Clustering

  18. Grapheme Based Synthesis � Synthesis without a phoneme set Synthesis without a phoneme set � � Use the letters as phonemes Use the letters as phonemes � � (“ (“alan alan” nil (a l a n)) ” nil (a l a n)) � � (“black” nil ( b l a c k )) (“black” nil ( b l a c k )) � � Spanish (easier ?) Spanish (easier ?) � � 419 utterances 419 utterances � � HMM training to label databases HMM training to label databases � � Simple pronunciation rules Simple pronunciation rules � � Polici’a Polici’a - -> p o l i c i’ a > p o l i c i’ a � � Cuatro Cuatro - -> c u a t r o > c u a t r o �

  19. Spanish Grapheme Synthesis

  20. English Grapheme Synthesis Use Letters are phones Use Letters are phones - - 26 “ “phonemes phonemes” ” 26 - - ( “ ( “alan alan” ” n (a l a n)) n (a l a n)) - - ( “ “black black” ” n (b l a c k)) n (b l a c k)) ( - - Build HMM acoustic models for labeling Build HMM acoustic models for labeling - - For English For English - - “This is a pen This is a pen” ” “ - - “We went to the church at Christmas We went to the church at Christmas” ” “ - - Festival intro Festival intro - - “do eight meat do eight meat” ” “ - - Requires method to fix errors Requires method to fix errors - - Letter to letter mapping Letter to letter mapping - -

  21. Signal Processing for TTS Pitch and duration modification � Pitch and duration modification � LPC � LPC � Finding the right unit type � Finding the right unit type � Grapheme- -based Synthesis based Synthesis � Grapheme �

  22. HW1: TTS Due 3:30pm Friday October 2 nd nd � Due 3:30pm Friday October 2 � Install Festival and Festvox Festvox � Install Festival and � Find 10 errors in each of two different � Find 10 errors in each of two different � synthesizers synthesizers Build a voice � Build a voice � � A Talking Clock A Talking Clock � � A general voice A general voice � � (or both) (or both) �

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