Systems, Man & Cybernetics - January 2016 - 11

Place of Articulation Dental (/ /, /θ/)

Alveolar (/t/, /d/)

Retroflex (/r/, / /)

Palato-Alveolar (/ /, / /)

The Position of the
Tongue

Related Articulators Tongue Tip or Blade
Tongue Tip and the
and Upper Front Teeth Alveolar Ridge
Example Words
The Spatial Pattern
of Evoked Potential
Difference

"thigh," "thy"
(µV)

Place of Articulation Palatal (/ /, / /)

20
10
0
−10
−20

"tie," "die," "nigh"
(µV)

Velar (/g/, /k/)

The Position of the
Tongue

Tongue Tip and the Back Tongue Blade and the
of the Alveolar Ridge
Back of Alveolar Ridge
"rye," "ray"

6
3
0
−3
−6

"shy"
(µV)

20
10
0
−10
−20
Bilabial (/m/, /b/, /p/)
Oral Cavatiy

Tongue

(µV)

Alveolar
Ridge
Lips

Tongue

Back of the Tongue
Made with the Two Lips
Related Articulators Front of the Tongue
and Hard Palate
and Soft Palate
"you"
"guy," "kite"
"my," "buy," "pie"
Example Words
15
(µV)
(µV)
(µV)
4
10
The Spatial Pattern
10
2
5
5
of Evoked Potential
0
0
0
−5
Difference
−5
−2
−10
−10
−15
−4

10
5
0
−5
−10

Hard Palate
Soft Palate

Teeth
The places of articulation
used for vocalization
with the tongue.

Figure 3. tongue positions and gKP patterns for eight representative places of articulation.

whose length was 2 s (1 s for /a/ and another second for
the consonant phonemes). Then, we segmented the signals from 0.5 to 1 s corresponding to /a/ without GKP
and the signals from 1.5 to 2 s corresponding to each
consonant phoneme, which included GKP responses.
From two segmented signals, we calculated the difference between their mean values in each channel. We
calculated the mean values from the signals for four
subjects, and their grand averages were visualized in
Figure 3 using the EEGLAB topoplot function [17]. For
enhancing the visibility, we applied different scale ranges for each plot, and we depicted the ranges on the right
side of each plot.
From the results, we observed that, when pronouncing
dental, palato-alveolar, and palatal consonants, the potential levels in the channels on the frontal region decrease,
whereas the potentials on the occipital region increase.
The results from alveolar and velar consonants also
showed the potential decrease in the frontal region, but the
magnitude of decrease was smaller than the cases for the
above three consonants. In opposition to the aforementioned consonants, pronouncing the retroflex consonant
showed a potential increase in the frontal region and a
decrease in the occipital region. It implies that upward
tongue movements to the articulators, such as the teeth,
alveolar ridge, and palate, evoke the potential decrease in
the frontal region and the increase in the occipital region.

However, if the tongue is bent for pronouncing the retroflex consonant, a strong potential increase is observed in
the frontal region.
Potential Applications of the
Investigated GKP Pattern
We believe that surveyed results could be beneficial for
researchers in various fields [14]. First, it can provide a
new technique to trace language-related tongue movements for speech scientists. A fast and reliable technique to trace tongue movements is important for
speech scientists who try to understand how speech is
controlled by the tongue or how the tongue is disrupted
in various speech disorders [18]. For years, speech scientists have developed several methods exploiting
tagged magnetic resonance imaging (MRI) and electromyography (EMG) to trace the tongue movements during speech production. However, the MRI requires an
expensive device and facility including a shielded room,
and the EMG has difficulties in measuring the activations of small intrinsic muscles, such as the transversus
and verticalis. These muscles are located deep inside
the tongue body, thus, it is difficult to measure their
activations directly from EMG signals [18]. GKP can
provide a simple and cost-effective method to trace
tongue movements that is able to detect the contact of
the tongue with other articulatory organs.
Ja nu a r y 2016

IEEE SyStEmS, man, & CybErnEtICS magazInE

11



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