H. Strik & L. Boves (1992a)
Journal of Phonetics 20, pp. 15-25.
This article has appeared in the Journal of Phonetics. Therefore, I only
have a printed version with the final text and the final layout. If you
want a copy of this article, you can find it in Journal of Phonetics 20,
or you can contact me. The text of the ASCII version
below is slightly different from the text of the article.
Running title: Control of F0, IL and voice quality
In this paper the control of fundamental frequency (F0), intensity level
of the radiated acoustic signal (IL), and voice quality is studied in normal
conversational speech. It is shown that the physiological factors that best
explain measured features of the speech wave depend on the part of the utterance
taken into account. Also, it appears that in speech transglottal pressure
(Ptr) is more important than subglottal pressure (Psb). We conclude that
currently available mathematical models that describe the waveform of glottal
volume flow (Ug) lack a number of parameters necessary for a better understanding
of the physiological control of the speech parameters investigated in this
The relation between Psb and laryngeal configurations on the one hand, and
F0, IL, and Ug on the other is extremely complex. Moreover, Psb and especially
laryngeal configurations and the ways in which they are brought about are
difficult to measure. Perhaps due to the measurement problems most investigations
of laryngeal control and its effects on the radiated acoustic signal have
dealt with sustained vowels produced in widely different ways, rather than
with "normal" speech production. In many studies F0 was varied over several
octaves and Psb over a range from approximately 5 cm aq. to well above 30
cm aq. There are several reasons why the results obtained in those studies
may not directly be applied to speech production. In "normal neutral" speech
the ranges are much smaller. This may imply that some of the control mechanisms
needed to span the wide ranges in 'phonation experiments' are much less
important in speech. Also, in sustained vowels oral pressure (Por) may be
considered equal to atmospheric pressure. But in speech production, where
non-negligible constrictions of the vocal tract occur, Por is much more
important. In the present study we have looked into the relation of laryngeal
characteristics to IL and F0 in normal speech. We will touch upon some methodological
aspects of the research. Also, we will pay due attention to the role of
Por and Ptr.
2. Material and methods
2.1. Experimental procedure
The subject in this study was a male native speaker of Dutch, with no experience
in phonetics or linguistics and with no history of respiratory or laryngeal
dysfunction. During the production of various utterances (sustained vowels,
sentences with different intonation patterns) simultaneous recordings of
the acoustic signal, electroglottogram (EGG), lung volume (Vl), Psb, Por,
and electromyographic (EMG) activity of the sternohyoid (SH) and vocalis
(VOC) muscles were obtained. Near the end of the recording session he was
asked to produce an utterance spontaneously. He replied by saying (in Dutch):
"Ik heb het idee dat mijn keel wordt afgeknepen door die band" (I have the
feeling that my throat is being pinched off by that band). After he spoke
this sentence, he was asked to repeat it 29 times.
2.2. Data recording
The speech signal was transduced by a condenser microphone (B&K 4134) placed
about 10 cm in front of the mouth, and amplified by a measuring amplifier
The EGG was recorded with a Fourcin-Abberton laryngograph (Fourcin, 1974).
The pressure signals were recorded using a Millar(R) catheter with four
miniature pressure transducers, in the way described by Cranen and Boves
(1985). The catheter was introduced into the pharynx via the nose, and then
into the trachea via the posterior commisure. It did not have a noticeable
effect on phonation (Boves, 1984).
The EMG signals were recorded using hooked-wire electrodes (Hirose, 1971).
The electrodes were inserted percutaneously, and correct electrode placement
was confirmed by audio-visual monitoring of the signals during various functional
The perimeter of chest and abdomen were measured with mercury filled strain-gauge
wires (Strik and Boves, 1988).
All signals were recorded on a 14-channel instrumentation recorder (TEAC
XR-510), using a bandwidth of 5 kHz.
2.3. Processing of the data
All signals were A/D converted off-line at a 10 kHz sampling rate. The files
were stored on a microVAX computer. Because of the sluggishness of the articulators
it seems sufficient to use a sampling frequency of 200 Hz. Therefore, the
goal of preprocessing is to derive physiological signals which all have
a sampling rate of 200 Hz.
F0 and IL were calculated with the SIF program of ILS. Both values were
calculated every 5 ms, resulting in F0 and IL signals sampled at a 200 Hz
Pressure signals, chest and abdomen signals were low-pass filtered and downsampled
to 200 Hz. Lung volume was calculated from the low-pass filtered chest and
The integrated rectified EMG was calculated in the way described by Basmajian
(1967): first the signal is full-wave-rectified, and then it is integrated
over successive periods of 5 ms. The integrator is reset after each integration.
Finally, the signal is smoothed by convolving it with a triangular function
(base length 35 ms).
There is a time delay between the change of the electric potential of a
muscle and the resulting effect in the acoustic signal (Atkinson, 1978).
To overcome this delay, all EMG signals were shifted forward over their
mean response times.
After preprocessing median signals were calculated with the method of non-linear
time-alignment that is described in Strik and Boves (1991), in which the
fifth repetition was used as a reference.
2.4. The parameters of the glottal volume flow
There are a number of different ways to parameterize the glottal volume
velocity waveform (Klatt & Klatt, 1990; Fant, 1986; Cranen & Boves, 1987).
Although we do not believe that it is the best model from a physiological
point of view, we will use the Liljencrants-Fant (LF) model in this paper,
mainly because it seems to be the model used in most recent studies. It
seems that many of the features of this model are motivated from a perceptual
point of view, i.e. by the ease with which they allow one to approximate
or explain (spectral) characteristics of the speech wave that are important
from a perceptual point of view. However, most of the parameters can also
be related to what is known about the physiology of phonation. Specifically,
the LF-model allows one to describe the maximum amplitude of the flow during
the open glottis interval (U0), the duty cycle of the flow pulses, the amount
of skewing of the pulses, the amplitude of dUg/dt at the moment of glottal
closure (Ee) and the time delay between the moment of major vocal tract
excitation and the instant where the glottal flow becomes quasi-constant
2.5. Calculation of glottal volume flow
Of course, no direct recordings of the glottal volume flow were made; this
signal is derived from the speech waveform by means of inverse filtering.
Closed Glottis Interval Covariance LPC was used to estimate the parameters
of the inverse filter. In de Veth, Cranen, Strik, and Boves (1990) it was
shown that this procedure outperforms more complicated ones that attempt
to estimate the parameters of the inverse filter by means of Robust ARMA
Inverse filtering yields an estimate of dUg/dt. Integration of this signal
gives the flow signal. For the present article we only wanted to measure
peak glottal flow U0, excitation strength Ee, and Ptr for each voiced period.
The value of Ee is obtained by taking the minimum of the differentiated
flow in each pitch period. Likewise U0 is found by looking for the maximum
of the flow signal. Ptr is measured at the moment of maximum glottal flow.
Its value is obtained from a low-pass filtered pressure signal.
Inverse filtering was done on the fifth utterance, because that is the one
that is used as a reference in the method of non-linear time-alignment.
Inverse filter results were obtained for all voiced periods, including vowels
and voiced consonants.
3.1. Control of fundamental frequency
The relation between Psb and F0 has been the object of quite a number of
experimental (e.g. Atkinson, 1978; Collier, 1975; Maeda, 1976; Strik and
Boves, 1989) and modelling studies (e.g. Ishizaka and Flanagan, 1972; Titze
and Talkin, 1979). Yet, the details of this relation remain unclear. Estimates
of the F0 to Psb ratio from speech and special phonation tasks resulted
in values between 5 and 15 Hz/cm aq. (Collier, 1975; Maeda, 1976; Strik
and Boves, 1989). In another type of experiment pressure variations are
induced externally. The F0 to Psb ratios measured in these experiments tend
towards values of 2-5 Hz/cm aq. (Baer, 1979; Strik and Boves, 1989). Strik
and Boves (1989) showed that the ratio of an F0 change resulting from a
Psb change alone probably is the same in both experiments, viz. 2-5 Hz/cm
aq. In "normal" speech there are other factors that control F0, especially
the laryngeal muscles. Due to the simultaneous operation of these factors
the ratio of total F0 change to Psb change in utterances is often larger
than 2-5 Hz/cm aq. The latter ratio is in agreement with the ratio of 2-3
Hz/cm aq. that was found by Ishizaka and Flanagan (1972) for their self-oscillating
Furthermore, it seems that in most experiments, and therefore in most presently
existing models, the effects of Por on F0 are not sufficiently taken into
account. Probably this is due to the fact most experiments were done with
sustained vowel phonation, in which the variation in Por is much smaller
than in normal speech. Strik and Boves (1988) studied the relation of F0
to Psb, Por, and Ptr in connected speech. The median signals for the 29
sentence repetitions of this experiment, obtained with the method of non-linear
time-alignment, are shown in Fig. 1. These signals were used to calculate
correlations between the variables of interest. In Table I the correlations
are given for a long voiced interval, while Table II contains the same correlations
for all voiced frames.
The most important conclusion that can be drawn from the data in Tables
I and II is that the pattern of correlations between Psb, Por, Ptr, and
F0 depends very much on the part of the utterance over which the measurements
are taken. If measurements are limited to a single voiced interval, Ptr
(and Por) are much better predictors of F0 than Psb (see Table I). When
measured over a complete utterance, however, Psb and Ptr explain essentially
the same proportion of the variation in F0 (see Table II). This is due to
the fact that the range of Psb in individual voiced intervals is rather
small (see Table I). The range spanned by Ptr, on the other hand, is much
wider, because of the fact that Por varies between Psb in voiceless stops
and zero in open vowels. In a complete declarative utterance, on the other
hand, the correlation between Psb and F0 is much enhanced by the fact that
both show some amount of declination. The data in the Tables were obtained
from a single subject and therefore should be verified on a larger population.
Yet, from a physiological point of view (as well as on statistical grounds)
they seem to be quite plausible.
Our results show that one must be very cautious in interpreting the outcomes
of experiments on physiological control of F0 (and all other speech parameters,
for that matter). Such caution is, of course, the more necessary with respect
to single subject studies, like our present study. One must be especially
cautious in generalizing the results of experiments to other situations
than those under which they were obtained. In fact, only results that can
be explained by a fairly comprehensive model may be generalized to situations
where a similar model can be assumed, operating in the same regime. We are
confident that the conclusion of our investigation are supported by a sufficiently
3.2. Control of Intensity and Voice Quality
Even if the relation between Psb and F0 has received some attention in the
literature, one still must be aware that the effects of Psb and laryngeal
configurations are not limited to F0; on the contrary, factors like the
acoustic power generated at the glottis and the waveshape of the glottal
volume flow pulses are also affected. These relations are much less studied.
That may, at least in part, be due to the assumption that voice intensity
and voice timbre are of less importance from a linguistic point of view.
However, if it comes to a better understanding of the fundamentals of phonation
and of para-linguistic phenomena like voice quality and its variations,
radiated intensity and details of the glottal volume velocity waveform become
of crucial importance. In the present study we contribute some measurement
data related to control of IL and voice quality obtained from connected
speech and show how these data can fit in with modelling research.
3.2.1. The relation between IL and Pressure
It has long been known that there must be a relation between Psb and IL,
if only because Psb is the major source of phonatory energy (cf. Rubin,
1963). Most measurement data on the relation between Psb and IL seem to
stem from in vitro experiments, however, or at best from experiments where
sustained vowels were produced with intensity and pressure variations spanning
a range larger than usually found in speech (e.g. Bouhuys, Mead, Proctor,
and Stevens, 1968; Cavagna and Margaria, 1968; Isshiki, 1964; Tanaka and
In our own investigation of the best predictor of IL in the production of
voiced speech sounds, we found that Ptr outperforms Psb by far (Strik and
Boves, 1988). The result is true both on a local (i.e. within words or voiced
intervals) and on a global level (i.e. looking over complete utterances).
In both situations the correlation between Ptr and IL exceeds 0.92, while
the correlation with Psb is at most 0.49 (when measured over a complete
sentence, see Tables I and II). So, at least for this subject, it seems
that Ptr is more important in the control of IL than Psb.
Bouhuys et al. (1968), Cavagna and Margaria (1968), Isshiki (1964), and
Tanaka and Gould (1983) all found high correlations between IL and the logarithm
of Psb when subjects produced sustained vowels. For sustained vowel phonation
Por is almost constant and close to zero and, as a result, Ptr is almost
equal to Psb. In our data Por, Ptr, and IL vary quickly and considerably,
while Psb decreases slowly during the course of the utterance (Fig. 1).
This explains why in our data the relation between IL and Psb is rather
Except for the correlation the regression coefficient is also of importance,
because it predicts the amount of change in IL due to a given change in
Ptr. In order to be able to compare our findings with previous results we
calculated the regression equation between IL and the logarithm of Ptr.
Based on the 293 voiced frames of the median signals of the current experiment
(see Fig. 1) we found the following relation
IL = 41.6 + 30.3*log(Ptr) (N = 293, R = 0.90)
Or, in other words, the intensity (I) of the radiated speech wave is proportional
to Ptr to the power 3.03. Interestingly enough the value of the power in
the resulting relation between I and Ptr is quite comparable to results
reported in the literature about the relation between I and Psb. For sustained
vowel phonation Cavagna and Margaria (1968) found a value of 3.0 +/- 1.0,
Isshiki (1964) found a value of 3.3 +/- 0.7, and Tanaka and Gould (1983)
found a value of 3.18; while Bouhuys et al. (1968) reported a value of 3.0
At a first glance it seems strange that comparable regression equations
are found for different relations (IL and Ptr vs. IL and Psb), obtained
for different kinds of speech (normal conversational speech vs. sustained
phonation) and different ranges of IL and pressure (2-7 cm aq. vs. 2-60
cm aq.). But closer inspection reveals that both relations are not really
different. For sustained vowel phonation, and singing of constant tones,
Por usually is close to zero and Psb and Ptr are almost equal. Therefore,
for these modes of phonation, the relations between IL and Ptr and between
IL and Psb are very similar. The conclusion is that the relation between
IL and Ptr obtained by Bouhuys et al. (1968), Cavagna and Margaria (1968),
Isshiki (1964), and Tanaka and Gould (1983) for sustained phonation and
large ranges of IL and Psb is comparable to the relation obtained in this
experiment for normal conversational speech.
It may still be that Psb is an important factor in the control of IL, certainly
if it is varied over ranges that are much wider than normally found in conversational
speech but that are not unusual in singing or in very loud speech. But our
data suggest that the faster variations of IL related to articulatory manoeuvres
are primarily determined by variations in Por that cause similar variations
in Ptr, whereas the gradual decrease of IL observed during many (declarative)
utterances in a large number of languages is caused by a gradual decrease
in Psb. The finding that IL is mainly controlled by Ptr makes it interesting
to further investigate the detailed way in which IL is influenced by Ptr
via the characteristics of the glottal volume flow.
3.2.2. Flow waveform characteristics and Ptr
From the literature it is known that the parameters Ee and U0 in the LF-model
have most effect on IL (Gauffin and Sundberg, 1989). Thus we measured Ee
and U0 for all 181 pitch periods of the fifth repetition, for which reliable
inverse filter results could be obtained. Most of these periods pertained
to vowels, but a substantial part comes from voiced consonants. We wanted
to examine the relation of Ee and U0 to Ptr.
The relation between Ee and Ptr is shown in Fig. 2a. It seems as if this
relation shows three different regimes. The bulk of the samples (148 out
of a total of 181) falls into the category of, what we call, steady phonation.
For the data of this category an exponential fit (R = 0.79, see Fig. 2a)
is slightly better than a linear fit (R = 0.73). The second category consists
of the pulses in V-UV transitions (i.e. both V/UV and UV/V transitions).
For this category Ee is often relatively lower, compared to steady phonation,
especially at the beginning of voicing. On the other hand, for the vowel
/a/ from the very last syllable of the utterance, Ee is relatively higher
(the reasons for taking the utterance final syllable apart are more fully
explained in section 3.3).
The correlation between U0 and Ptr is depicted in Fig. 2b. Again, for the
data of the category 'steady phonation', an exponential fit (R = 0.72, see
Fig. 2b) is somewhat better than a linear fit (R = 0.65). The data for the
vowel /a/ of the last syllable still deviate considerably from the regression
line, while the data for V-UV transitions are scattered on both sides of
the regression line.
From a look at the spectra of the glottal flow waves it is immediately apparent
that the spectral slopes in the three regimes are quite different. In the
pitch pulses taken from vowel onsets and from the final stressed syllable
the spectral tilt is much steeper than in the central pitch periods of the
vowels taken from the beginning and middle of the utterance. The slope difference
is more than large enough to have clear perceptual consequences. Thus, the
observed effects in voice quality are of sufficient interest to take them
into account in the description of speech production and to model them in
high quality speech synthesis.
Although Ee and U0 appear as separate parameters in the LF-model, they are
not unrelated themselves, since Ee is dUg/dt at the moment of major excitation.
Thus, if U0 increases, Ee should also increase, everything else being equal.
Therefore, we looked at the relation between Ee and U0, which is shown in
Fig. 2c. For steady phonation the correlation between Ee and U0 is very
high (viz. 0.80). Apparently the effect of other parameters (like T0, skewness,
and duty cycle) on this relation is not large in "normal" speech.
3.3. The utterance final syllable
Towards the end of the utterance F0, IL, Ptr, and Psb decrease substantially,
while there is a marked increase in the SH activity during the last syllable
(see Fig. 1). This phenomenon, the so called final fall, is observed more
often (Collier, 1975; Maeda, 1976; Strik and Boves, 1989). Presumably, the
larynx returns to its rest position, and the lowering of the larynx already
starts before phonation has stopped (Maeda, 1976). One would expect that
these gross changes in the posture of the larynx should affect the mode
of vibration of the vocal folds. This observation motivated a seperate study
of the glottal flow pulses in the utterance final vowel.
The fact that the characteristics of the vowel in the utterance final syllable
deviate from those of the preceding vowels was also observed by Klatt and
Klatt (1990). For the last syllable they found increased noise in the F3
region of the spectrum, indicating a greater glottal airflow. But they also
found a weaker first harmonic (relative to the amplitude of the second harmonic)
in an utterance final syllable, indicative of a pressed voice with a slightly
smaller open quotient. Therefore they introduced a novel breathy-laryngealized
mode of vibration.
We tried to verify their hypothesis by comparing the data of the (stressed)
vowel /a/ of the last syllable, with the data of the first (unstressed)
vowel /a/ in the utterance. The spectrum of the utterance final vowel indeed
showed increased noise at frequencies above roughly 1.4 kHz. But the amplitude
of the first harmonic (relative to the amplitude of the second harmonic)
was about 1.5 dB stronger, and the open quotient was approximately 50% in
both vowels. Consequently, there is evidence for a breathy mode of phonation
at the end of this utterance, but not for laryngealization.
Generally, everything else being equal, a decrease in Ptr would lead to
a decrease in U0 (Ishizaka and Flanagan, 1972). Ptr decreases from 5.5 cm
aq. for the first vowel /a/, to 4.2 cm aq. for the last vowel /a/, but the
amplitude of the AC-component of glottal flow (U0) increases with roughly
6%. Substantial differences in the degree of adduction are not likely, since
the open quotient is about 50% in both vowels. Presumably in the utterance
final vowel the vocal folds are slackened, either to facilitate the maintenance
of voicing with decreased Ptr, or due to a general relaxation of muscular
activity and a preparation for breathing at the end of an utterance.
Comparing both vowels /a/ it is observed that there is a decrease in Ee
of approximately 14% in the last vowel, even though U0 increases slightly.
We found that, generally, the effect of other parameters (like T0, skewness,
and duty cycle) on the relation between Ee and U0 is not very large for
the data of the present experiment (see Fig. 2c). But for the last vowel
/a/ T0 is substantially larger than T0 of the first vowel /a/. After correction
for this temporal difference, i.e. when the same number of flow pulses are
plotted on the same horizontal scale for both vowels, no major differences
in the shape of the glottal volume flow are observed. Consequently, the
change in U0 (+6%) combined with the change in F0 (-20%) determines the
change in Ee (-14%). The fact that, apart from time-stretching, no major
differences were found in duty cycle and shape of the glottal pulses between
both vowels /a/, also indicates that the degree of adduction has not changed
In this paper we have shown that the control of F0, IL and voice quality
in normal speech may be somewhat different from what is known from the literature
on studies based on sustained vowels or singing. In speech Ptr seems to
be more important than Psb, mainly because Por cannot be considered as constant
and negligible. Also, it was shown that the relative importance of physiological
parameters that affect F0, IL and voice quality depends very much on the
nature of the speech from which they are derived. Although the results are
based on a single subject study, they fit in very nicely with current models
of the physiology of phonation.
Especially from the results on the control of IL and voice quality it became
clear that descriptive mathematical models of the glottal flow waveform
do not allow one to make the step from description to explanation. High
correlations were found for Ee and Ptr, and for U0 and Ptr. But in the LF-model
there is no relation between Ee and Ptr, or between U0 and Ptr, for the
simple reason that Ptr does not figure in the model. Thus, the LF-model
will never allow one to explain these relations, or why several different
regimes should exist in the relation between Ptr and basic parameters in
the model. One will have to take recourse to models that have a firm physiological
basis, like the ones proposed in Titze (1984) and Cranen (1990).
This research was supported by the Foundation for linguistic research, which
is funded by the Netherlands Organization for Scientific Research, N.W.O.
Special thanks are due to Philip Blok M.D. who inserted the EMG electrodes
and the catheter in the present experiment.
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Figure 1. Median physiological signals, obtained by the method of non-linear
time-alignment. Plotted are, from top to bottom, F0, IL, Ptr, Por, Psb,
Vl, SH, and VOC.
Figure 2. Scatterplots of respectively (a) Ee and Ptr; (b) U0 and Ptr; and
(c) Ee and U0. Given are regression lines for exponential or linear fits,
and the correlation coefficients for the fits for the data of the category
'steady phonation'. Ee and U0 values are given relative to the maximum observed
value for each quantity.
Table I. Correlation matrix, means and standard deviations of the median
physiological signals for a voiced interval (N=66, |R|>0.315 for p<0.01).
F0 IL Ptr Por Psb mean SD
F0 1.000 0.808 0.851 -0.783 0.478 118.58 3.70
IL 1.000 0.960 -0.983 0.111 63.23 3.38
Ptr 1.000 -0.968 0.274 5.42 0.88
Por 1.000 -0.054 1.16 0.91
Psb 1.000 6.35 0.16
Table II. Correlation matrix, means and standard deviations of the median
physiological signals for all voiced frames (N=293, |R|>0.151 for p<0.01).
F0 IL Ptr Por Psb mean SD
F0 1.000 0.667 0.729 -0.153 0.772 115.87 8.59
IL 1.000 0.923 -0.663 0.492 62.20 4.25
Ptr 1.000 -0.638 0.612 4.95 1.17
Por 1.000 0.211 0.89 0.95
Psb 1.000 5.65 0.90