Analysis and Digital Implementation of the Talk Box Effect

Yuan Chen

Advisor: Professor Paul Cuff

Introduction What is a talk box?

Allows a musician to add diction and intelligibility to an instrument’s sound

Motivation? Popular as an analog

device Application of signal

processing Goals?

Analyze output Digital

implementationFigure 1 – Talk Box

Background – Speech and Intelligibility Human speech production of convolution

between source and filter (1)

Not really time invariant Only valid for voiced speech

Frequencies of formant peaks account for intelligibility of speech (Lingard, McLoughlin) Most important are F2, F3 formants which occur in

frequency band 800 Hz – 3 kHz

)()()( nnens

Complex Cepstrum Formant peaks arise from , need a way to

“deconvolve”

Intuitively source excitation varies quickly in frequency, vocal tract response varies slowly in frequency (Deller)

Complex Cepstrum (eq. 2) (Deller):

Apply a low quefrency lifter to separate source and filter

deSn njs )(log

2

1)(

Analysis Results – Vowel Sounds Talk box most successfully impresses F2, F3

peaks Relative Error in peak frequency: F1 – 19.6%, F2 –

9.33%, F3 – 6.22% Error due to inability to replicate sound

For voice, ~90% of energy in 0 Hz – 1000 Hz For talk box, ~10% of energy in 0 Hz – 1000

Hz

Design Overview Problem definition:

Implement in MATLAB

Vocal Tract Impulse Response Extraction

Calculate cepstrum (eq. 3):

Lifter: Eliminate all quefrency above cutoff nc (eq. 4)

From liftered cepstrum, invert to calculate impulse/frequency response (eq. 5):

Impulse Response Preprocessing Calculated impulse response has too high low

frequency (0 – 1000 Hz) magnitude

Different frames of speech have different energy levels Speech input should not directly determine output

amplitude

Normalize, preprocess in frequency domain (eq. 6):

Synthesis 50% overlap between successive frames

Define system response to be linear interpolation of vocal tract impulse responses in overlapping region (eq. 7):

α: relative index (eq. 8)

p: frame index (eq. 9)

Synthesis From causality, output at time n0 depends only

on input occurring no later than n0

From finite-length impulse response, output at time n0 depends only on input occurring no earlier than n0 – M + 1

Closed Form expression for y(n) (eq.11):

Design Summary

Performance F2, F3 peaks on vowel speech inputs:

Static implementation relative error: 3.0% F2, 3.5% F3

Dynamic implementation relative error: 3.7% F2, 3.2% F3

Qualitatively, output has similar intelligibility to analog talk box

Dynamic implementation can produce voiced non-vowel phonemes and whole words Not always consistent, depends on alignment in

time

Performance Issues Even with linearly-interpolated system

impulse response, noticeable transitions between frames

Computationally expensive: 2 FFTs, 2 IFFTs per frame In MATLAB, computation time takes longer than

duration of the frame

Performance dependent on alignment of input signals

Conclusions and Further Considerations Dynamic implementation closely models

performance of analog talk box: Can produce vowels and voiced phonemes Real-time setup

Demonstrate possibility of fully digital implementation of talk box using speech input

Further considerations: Improve transitions between frames Decrease calculation time Physical implementation