Outline  Introduction  Applications  History of time and pitch modification  Time-domain techniques  Frequency-domain techniques  Parametric techniques

1. Prepared by:
Doaa Gamal
Lecturer Assistant
Faculty of Engineering – Suez Canal University
1

2. Outline
 Introduction
 Applications
 History of time and pitch modification
 Time-domain techniques
 Frequency-domain techniques
 Parametric techniques
 conclusion
2

3. Introduction
 Timescale modification: slow down or speed up a given
signal, possibly in a time-varying manner, without
altering the signal’s spectral content (and in particular
its pitch when the signal is periodic).
 pitch-scale modification: the aim is to modify the
pitch of the signal, possibly in a time-varying manner,
without altering the signal’s time-evolution (and in
particular, its duration).
3

4. Introduction
 time-scaling or pitch-scaling is not easy because time
and frequency characteristics of a signal, being related
by the Fourier transform, are not independent.
 the simplest method of time scaling a sound is to just
replay it at a different rate. When using magnetic
tapes, for example, the tape speed may be varied, but
this incurs a simultaneous change in the pitch of the
signal.
4

5. applications
 Speech Synthesizers
 Post-synchronization
 Data compression
 Reading for the blind:
 Foreign language learning
 Voice transformation
5

6. History of time and pitch modification
Signal
type
method technique
Analog tape recorder machine Time-domain
Digital Digital tape recorder Time-domain
Digital Periodicity-driven
methods
Time-domain
Digital STFT Frequency-domain
Digital Linear prediction models
& sinusoidal models
parametric models
6

7. time and pitch modification
techniques
Non-
parametric
Frequency-
domain
techniques
Time-domain
techniques
Parametric

8. Time-domain techniques
Pitch independent methods
 requires very few calculations
 very well to real-time
implementation.
 prone to artifacts because no
precaution is taken at the
splicing points, other than to
guarantee continuity.

9. Time-domain techniques
Periodicity-driven methods
The most popular method using pitch information is
TD-PSOLA
modification factors (between 0.5 and 2).

10. TD-PSOLA analysis-synthesis
process without modification
1 2
3

11. TD-PSOLA analysis-synthesis
process without modification
The output speech waveform of PSOLA analysis-synthesis is
perceptually indistinguishable from the original waveform.
4

12. pitch-scaling (lowering) using
TD-PSOLA
12

13. time-scaling (lengthening) using
TD-PSOLA
13

14. Computation of synthesis pitch-
marks for pitch modification
14

15. Computation of synthesis pitch-marks
for pitch modification (raising)

16. Computation of synthesis pitch-
marks for duration modification
16

17. Computation of synthesis pitch-marks for
time-scale modification (lengthening)

18. From the synthesis pitch-marks to
the modified waveform
The simple way is
 calculate the nearest analysis pitch-mark to the virtual
pitch-mark is found
 The frames which corresponds to the nearest analysis
pitch-marks are centered on the synthesis pitch-marks.
 The overlapping regions are added together.
18

19. From the synthesis pitch-marks to
the modified waveform
19
• In more sophisticated systems, the mapping involves
linear interpolation between the two successive
short-time analysis signals lying the closest to the
virtual pitch-mark
 The perceptual quality of the prosody modified speech
using PSOLA methods depends on the accuracy of the
pitch markers estimation. As estimating epochs from
speech provide more accurate pitch marker locations

20. LP-PSOLA & FD-PSOLA
 The Frequency-Domain PSOLA (FD-PSOLA) and the
Linear-Predictive PSOLA (LP-PSOLA) approaches are
theoretically more appropriate than the time-domain
PSOLA method for pitch-scale modifications because
they provide independent control over the spectral
envelope of the synthesis signal.

21. Frequency-domain techniques
 Frequency-domain algorithms operate with a short-
time spectrum of the signal (phase-vocoder)
1. Calculate shift-time Fourier transform (STFT) of a
signal
2. Modify phases of each frequency channel.
3. Synthesize a signal using inverse STFT with a different
time stride
21

22. Parametric techniques
 linear prediction models
 sinusoidal models
 the Harmonic plus Noise Model, HNM
 wideband models
 STRAIGHT

23. conclusion
 Time-domain approaches are computationally cheap
and perform good for small modification factors.
 Good for real-time implementations
 possible to incorporate such systems in consumer
products such as telephone answering systems.
 suffering from echos.
 In particular, time or pitch-scale modifications by
large factors cannot be carried out by time-domain
methods and usually require the use of the more
elaborate frequency-domain techniques.
23

24. conclusion
 Frequency-domain techniques are capable of
providing very high quality output. However, they still
suffer from some distortion, mainly due to the effects
of “phase dispersion.”
 computationally intensive.
24

25. conclusion
 Parametric techniques tend to outperform non-
parametric methods when the adequation between the
signal to be modified and the underlying model is
good. When this is not the case however, the methods
break down and the results are unreliable.
 Parametric techniques usually are more costly in terms
of computations, because they require an explicit
preliminary analysis stage for the estimation of the
model parameters.
25