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Voice morphing

              Presented
                  By
          H.Mohammed.Sabir
             09AT1A0461

              Supervised
                  By
             Shreedhar Sir
SEMINAR OUTLINES

What   It is?
Need   of Voice Morphing
Description      the Morphing.
Technical       details of Morphing.
Application       areas.
What is Voice Morphing ??


   Voice morphing is a technique for modifying a (source)
    speaker's speech to sound as if it were spoken by a
    different (target) speaker.


   In Simpler terms it is being able to change the speech of
    one speaker to that of another speaker.


   Technology developed at the Los Alamos National
    Laboratory in New Mexico, USA by George Papcun


   Applications for Voice Morphing range from recreational
    ones to security ones.
What it actually performs ?
   It is a technique to modify a source speaker's
    speech to sound as if it was spoken by a target
    speaker.
   Voice morphing enables speech patterns to be
    cloned
   And an accurate copy of a person's voice can
    be made that can wishes to say, anything in the
    voice of someone else.
Need of voice morphing

   Text To Speech (TTS)
   In public speech systems
   For special effects ( just like video or image morphing is
    done ).
   To diminish Ethnical barriers.
How to Morph Voice ??


   We need to effectively change the pitch from that of a male
    speaker to that of a female speaker. If we reminisce the
    excitation signal has information about the speaker.

   We find the LPC coefficients for the Source and Target Signals
    and using these coefficients we are going to interpolate
    between the two Signals.

   We get the New LPC (linear predictive coding) coefficients
    using the formula

         new lpc coeff = [const*(lpc source) + (1-const)(lpc
    target)]

   0 <= const <= 1

                                                                     …
How to Morph Speech ?? (contd…)



    The pitch of a female speaker will be close to twice that of
     the male speaker. In our example the pitch of the male
     speaker is 141Hz and that of the female speaker is 210Hz.


    So we need to develop some time stretching algorithm so
     that we can implement pitch shifting. We obtain the residue
     of the source signal and stretch it according to the value of
     the const. The const indicates what is the position of morphed
     signal in between the source and target.


    For example if const = 0.2 then the morphed signal will be
     closer in pitch to the source signal and a value of 0.8 for const
     will result in a pitch that is closer to the target signal.
How do we shift the Pitch ??
   We break the residue signal into small windows and introduce fade in
    and fade out for each block. We recombine everything to form the pitch
    shifted signal. Based on the alpha we can time stretch the residue
    according to our requirements.




    How do we Morph finally ??

•   We now have the pitch shifted residue signal and the new
      LPC coefficients. We should resample the pitch shifted
      signal so that it is played at a faster rate. [Remember
      when we pitch shift then the residue will last longer]. If
      we inverse filter the resampled pitch shifted residue then
      we can effect morphing.
Block Diagram
Time Domain Plots of Source and Target featuring the Pitch
Matching and Warping

   DTW(Dynamic Time Warping)


    - Dynamic Time Warping (DTW) is used to
    find the best match between the pitch of
    the two sounds.
Signal Re-Estimation

   Loss during Signal re-estimation


    -Due to signals being transformation into the
    cepstral domain, a magnitude function is
    used. This results in a loss of phase
    information in the representation of the
    data.
Limitations
 
Lots   of normalizing problems.
Some     applications require extensive sound libraries.
Different   languages require different phonetics.
It   is very seldom complete.
Advantages

   Allows speech model to be duplicated and an exact
    copy of a person’s voice.


   Powerful combat zone weapon.
Disadvantages

   Use to pull out the useful information.


   It hides the actual identity of the user.
Conclusion
   The approach we have adopted separates the sounds into two
    forms:

    - Spectral   envelope information
    - Pitch and voicing information.
   Dynamic Time Warping
    - Aligns the sounds with respect to their pitches.
   Signal re-estimation algorithm.
    - Frames are converted back into a time domain
    waveform.
Application Areas
   Fake telephone conversations as evidence in courts of
    law.


   Powerful battlefield weapon.

    - Provide
            fake orders to the enemy's troops,
    appearing to come from their own
    commanders.
Future Scope
   Extending the functionality of tool.
    - Create a powerful and flexible morphing
    tool.

   Increased user interaction.
    - Graphical User Interface could be
    designed and integrated to make the
    package more ‘user-friendly’.
BIBLIOGRAPHY:
• Ye, H. and S. Young (2003). "Perceptually Weighted Linear
  Transformations for Voice Conversion". Eurospeech 2003,
  Geneva. 
• Ye, H. and S. Young (2004). "High Quality Voice Morphing".
  Int Conference Acoustics Speech and Signal Processing,
  Montreal, Canada. 
• High quality Voice Morphing Hui Yeand Steve Young.
• Quality-enhanced Voice Morphing
Thank you!!!
Questions??

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Voice morphing-101113123852-phpapp01

  • 1. Voice morphing Presented By H.Mohammed.Sabir 09AT1A0461 Supervised By Shreedhar Sir
  • 2. SEMINAR OUTLINES What It is? Need of Voice Morphing Description the Morphing. Technical details of Morphing. Application areas.
  • 3. What is Voice Morphing ??  Voice morphing is a technique for modifying a (source) speaker's speech to sound as if it were spoken by a different (target) speaker.  In Simpler terms it is being able to change the speech of one speaker to that of another speaker.  Technology developed at the Los Alamos National Laboratory in New Mexico, USA by George Papcun  Applications for Voice Morphing range from recreational ones to security ones.
  • 4. What it actually performs ?  It is a technique to modify a source speaker's speech to sound as if it was spoken by a target speaker.  Voice morphing enables speech patterns to be cloned  And an accurate copy of a person's voice can be made that can wishes to say, anything in the voice of someone else.
  • 5. Need of voice morphing  Text To Speech (TTS)  In public speech systems  For special effects ( just like video or image morphing is done ).  To diminish Ethnical barriers.
  • 6. How to Morph Voice ??  We need to effectively change the pitch from that of a male speaker to that of a female speaker. If we reminisce the excitation signal has information about the speaker.  We find the LPC coefficients for the Source and Target Signals and using these coefficients we are going to interpolate between the two Signals.  We get the New LPC (linear predictive coding) coefficients using the formula new lpc coeff = [const*(lpc source) + (1-const)(lpc target)]  0 <= const <= 1 …
  • 7. How to Morph Speech ?? (contd…)  The pitch of a female speaker will be close to twice that of the male speaker. In our example the pitch of the male speaker is 141Hz and that of the female speaker is 210Hz.  So we need to develop some time stretching algorithm so that we can implement pitch shifting. We obtain the residue of the source signal and stretch it according to the value of the const. The const indicates what is the position of morphed signal in between the source and target.  For example if const = 0.2 then the morphed signal will be closer in pitch to the source signal and a value of 0.8 for const will result in a pitch that is closer to the target signal.
  • 8. How do we shift the Pitch ??  We break the residue signal into small windows and introduce fade in and fade out for each block. We recombine everything to form the pitch shifted signal. Based on the alpha we can time stretch the residue according to our requirements. How do we Morph finally ?? • We now have the pitch shifted residue signal and the new LPC coefficients. We should resample the pitch shifted signal so that it is played at a faster rate. [Remember when we pitch shift then the residue will last longer]. If we inverse filter the resampled pitch shifted residue then we can effect morphing.
  • 10. Time Domain Plots of Source and Target featuring the Pitch
  • 11.
  • 12. Matching and Warping  DTW(Dynamic Time Warping) - Dynamic Time Warping (DTW) is used to find the best match between the pitch of the two sounds.
  • 13.
  • 14.
  • 15. Signal Re-Estimation  Loss during Signal re-estimation -Due to signals being transformation into the cepstral domain, a magnitude function is used. This results in a loss of phase information in the representation of the data.
  • 16. Limitations   Lots of normalizing problems. Some applications require extensive sound libraries. Different languages require different phonetics. It is very seldom complete.
  • 17. Advantages  Allows speech model to be duplicated and an exact copy of a person’s voice.  Powerful combat zone weapon.
  • 18. Disadvantages  Use to pull out the useful information.  It hides the actual identity of the user.
  • 19. Conclusion  The approach we have adopted separates the sounds into two forms: - Spectral envelope information - Pitch and voicing information.  Dynamic Time Warping - Aligns the sounds with respect to their pitches.  Signal re-estimation algorithm. - Frames are converted back into a time domain waveform.
  • 20. Application Areas  Fake telephone conversations as evidence in courts of law.  Powerful battlefield weapon. - Provide fake orders to the enemy's troops, appearing to come from their own commanders.
  • 21. Future Scope  Extending the functionality of tool. - Create a powerful and flexible morphing tool.  Increased user interaction. - Graphical User Interface could be designed and integrated to make the package more ‘user-friendly’.
  • 22. BIBLIOGRAPHY: • Ye, H. and S. Young (2003). "Perceptually Weighted Linear Transformations for Voice Conversion". Eurospeech 2003, Geneva.  • Ye, H. and S. Young (2004). "High Quality Voice Morphing". Int Conference Acoustics Speech and Signal Processing, Montreal, Canada.  • High quality Voice Morphing Hui Yeand Steve Young. • Quality-enhanced Voice Morphing

Editor's Notes

  1. MAHATMA GANDHI MISSION ENGINEERING COLLEGE,NOIDA
  2. MAHATMA GANDHI MISSION ENGINEERING COLLEGE,NOIDA