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Acoustic correlates of stress
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Stress (whether at the word or sentence level) is never marked by a single acoustic property. To make the stressed syllable stand out from its neighbours, it is produced with greater physiological effort on the part of the speaker than its unstressed counterpart. This extra effort affects a number of acoustic parameters:

These parameters differ in their degree of correlation with stress properties.

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[+] Temporal organization

An early study that examined the effect of stress on the durations of syllables and segments in Dutch can be found in Nooteboom (1972). Target items were non-words /pɑpɑpɑp/ and /papapap/, with short/ lax/ B-class vowel /ɑ/ and long/ tense/ A-class vowel /a/, respectively. These items were spoken with stress on the first, second and third syllable in turn, in carrier sentences such that they were either `accented' (with sentence stress) or `unaccented' (word stress only). A large number of tokens were produced by each of two male Dutch speakers for each of the 3 (stress position) × 2 (accentuation) × 2 (vowel length) = 12 non-word types (between 17 and 26 tokens per type by speaker SG; between 12 and 24 by speaker IS). Duration of all plosives /p/ in positions C1 to C4 were measured physiologically (rather than acoustically) using electronic switches that were activated by lip contacts, as were the durations of the vowels in V1, V2 and V3. A summary of the results is seen in figure 1. This figure plots the segment durations, in milliseconds (ms), of C1, V1, C2, V2, C3, V3 and C4, in this order, along the x-axis, with separate lines for items with initial, medial and final stress. The four panels are arranged by vowel length (rows) and by accentuation (columns).

[+] Intensity

The intensity of the sound pressure wave has long been considered as an acoustical correlate of stress. Intensity (or sound pressure) is proportional to the square of the amplitude of the speech waveform averaged over a moving time-window that is long enough to include two glottal pulses (typically with an integration time of 20 ms for the male voice range and 10 ms for a female voice). Absolute intensity is expressed in Watts per square inch (or dynes per cm2). However, since in speech we are not so much interested in absolute sound pressures as in relative differences between sound pressures, intensities are usually expressed in decibels (dB). When two intensities differ in terms of Watts by a 1:10 ratio, the stronger of the two has a 20 dB greater relative intensity; when the power ratio is 1:100, the relative intensity difference is 40 dB; when the ratio is 1:1000, the difference is 60 dB. So each time the absolute intensity difference is multiplied by 10, there is a 20 dB increase in intensity. The perceptual span between the weakest sound pressure that can be detected in silence (the threshold of hearing, axiomatically set at 0 dB) and the strongest sound pressure that can be tolerated without crossing the pain threshold is 120 dB. Generally, the dynamic range of a spoken utterance is rather restricted, somewhere in between 55 and 75 dB above the threshold of hearing. By screaming, intensity levels rise to some 85 dB, and by whispering low intensities in the 40 to 55 dB range are made available.

Intensities of speech sounds are unstable as they vary considerably (intensity drops in the order of 5 dB) when the speaker inadvertently turns his head or when some object momentarily intervenes between the speaker’s mouth and the listener’s ears. Intensity differences of similar magnitude have commonly been reported as correlates of stress. These differences are small but prove reliable correlates (i.e. with little variability) of sentence stress but are even smaller and less reliable when word stress is signaled (Van Katwijk 1974; Rietveld 1984; Sluijter and Van Heuven 1996; Sluijter 1995).

The relative effects of stress on the temporal make-up of the non-words are very similar for accented and unaccented items – although durations are consistently longer overall under sentence stress. Hardly any effects of stress can be seen in the final syllable (see also Extra below). There are very large differences in the durations of V1 and V2 depending on the stress position. When the item is spoken with initial stress, V1 is very long and V2 short (ratio V1/V2 > 1). With medial stress, this pattern reverses completely, with a very short V1 and a very long V2 (ratio < 1), while items with final stress have intermediate vowel durations for V1 and V2 (ratio ≈ 1). The crucial observation, however, is that the effect of stress position on the durations of the consonant segments, though small in absolute terms, appears to be quite consistent as well: it is nearly always the case that a C, whether onset or coda, is somewhat longer on average in the stressed version of the syllable than in the unstressed version (i.e. in a paradigmatic comparison).

An experiment on a smaller scale involving both word and reiterant non-words in Dutch shows that the lengthening effect of stress is most clearly and consistently seen in the rhyme portions of the syllables (Sluijter and Van Heuven 1995). The effect of stress on onset consonants is less systematic or absent.

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Segments in a word-final syllable in Dutch are affected by domain-final lengthening but will not be lengthened any further when stressed. Unlike what happens in English, the effects of stress and final lengthening in Dutch are therefore not additive (Cambier-Langeveld and Turk 1999).

[+] Spectral balance

Accent in Western Germanic languages has often been equated with the expenditure of vocal effort, which is correlated with perceived loudness. The most obvious acoustic correlate of physiological effort and perceived loudness, it was commonly maintained, is vocal intensity. As is explained in articulatory correlates of stress, increased pulmonary effort causes a larger volume-velocity of airflow through the glottis. The result is not just the generation of larger glottal pulses but also, and more importantly, of a more strongly asymmetrical glottal pulse (figure 2). Typically, the closing phase of the glottal period is shortened, yielding a smaller opening quotient (OQ, the duty cycle of the glottal pulse, i.e. the proportion of the time the glottis is open relative to the period duration), and the trailing edge of the glottal period is steeper. The greater steepness of the glottal closure as well as its more abrupt ending cause the generation of relatively strong higher harmonics in the glottal pulse. As a result the spectral tilt of vocalic sounds produced with greater vocal effort emphasizes the higher frequencies. The spectral tilt of the glottal period produced with average effort has a -12 dB/octave roll-off (see Extra below). When speakers (or rather: singers) were asked to produce sustained vowel sounds with great vocal effort, the spectral tilt proved less steep, due to the fact that there was a relative boost of frequencies between 500 and 2000 Hz (Gauffin & Sundberg 1989). It has been shown that a similar phenomenon can be observed during the production of local vocal effort, i.e. during the production of a stressed syllable (Sluijter & Van Heuven 1993, 1996 for Dutch; see also Sluijter 1995).

Measuring the spectral balance (or tilt) is not without problems. Ideally, one needs to strip away the influence of resonances brought about by cavities in the supraglottal tract from the vocal output radiated from the mouth, so that the spectrum of the unfiltered glottal waveform is recovered. Once a clean glottal spectrum is available, the spectral tilt is a matter of fitting a simple linear regression function through the harmonics (plotted along a logarithmic frequency axis), and measuring its slope coefficient in dB/octave. Undoing the resonance effects of the vocal tract is done by inverse filtering. Inverse filtering software is now readily available (e.g. Airas et al. 2005) but the routines are not part of more comprehensive speech processing packages. In lieu of full-fledged inverse filtering, some fast-and-dirty approximations have been suggested by Stevens (1998) and were applied earlier in stress research by Sluijter et al. (1995), Sluijter & van Heuven (1996) and Sluijter (1995). When it is not necessary to know the absolute values of spectral tilt (e.g. when no comparison across different vowels is being made) a simpler approximation of spectral tilt is afforded by measuring intensity in four contiguous filter bands (one base filter from 0-0.5 KHz, and three contiguous octave filters: 0.5-1 KHz, 1-2 KHz, 2-4 KHz, cf. Gauffin & Sundberg 1989, Sluijter 1995). A linear regression line fitted through the four intensity levels at the filter bands' centre frequencies (plotted along a log frequency axis) yields the spectral tilt measure. In fact, we found that the intensity levels in the base and highest octave filter did not vary much as a function of accent level, so that a good substitute of spectral balance was obtained by just measuring mean vowel intensity (at the overall intensity peak) in the 0.5-2 KHz band (Sluijter and Van Heuven 1996; Sluijter 1995).

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When vowel sounds are radiated from the mouth some +6 dB/octave is added to the spectral slope, so that the spectral tilt of an average vowel equals –12 + 6 = –6 dB.

(graphs are based on Sluijter 1995 and Van Heuven 2001)

Figure 2

[click image to enlarge]

The effects of stress on spectral tilt at the sentence (left-hand column) and word level (right-hand column) can be seen in figure 3 for a paradigmatic comparison of selected syllables in the Dutch minimal stress pair canon[ˈkanɔn]canon, round ~ kanon[kaˈnɔn]cannon and reiterant mimicry by five male and five female speakers.


Figure 3: Effects of sentence (left column) and word (right column) stress on spectral tilt. Intensity (in dB) is plotted for four frequency bands (B1: < .5 KHz, B2: .5-1 KHz, B3: 1-2 KHz, B4: 2-4 KHz). Further see text

[click image to enlarge]

Figure 3 shows that generally no effects of stress can be observed in the base band (< .5 KHz). Effects are strong in the higher frequency bands, causing flatter spectral tilt, especially under sentence stress, and more clearly so in the initial syllable than in the final syllable.

[+] Spectral expansion

Stressed vowels have often been described as `clear' (spectrally expanded), reflecting greater articulatory effort and precision. These vowels lack the spectral reduction that is typical of unstressed vowels. Figure 5 (based on Van Bergem 1993) illustrates the effects of word and sentence stress on the expansion/reduction of long (tense) Dutch /eː oː aː/ read by 15 male speakers. The position of the schwa (averaged over 300 tokens across consonant environments and speakers) serves as the centre of gravity of the vowel space.

Spectral expansion is largest for vowels pronounced in isolation (`isol'). Some reduction is visible when these vowels occur in the stressed syllable of accented words (`+S+A' = sentence stress). Considerable reduction is seen for stressed vowels in unaccented words (`+S−A' = word stress) or for unstressed vowels in accented words (`−S+A'). Severe spectral reduction is found in unstressed vowels of unaccented words (‘!−S−A’): here the spectral distance to /«/ is minimal. Similar results were obtained for reiterant American English non-words by Sluijter & Van Heuven (1996) (for details see Sluijter 1995: 116-117).

(see text, after Van Bergem 1993)

Figure 4

[click image to enlarge]

Automatic classification by Linear Discriminant Analysis (LDA, see also Relative strength of stress correlates) of stress by spectral expansion of Dutch vowels was done by Sluijter & Van Heuven (1996) in the minimal stress pair canon[ˈkanɔn]canon, round ~ kanon[kaˈnɔn]cannon (see above) and their reiterant versions (of /nana/) produced in a short carrier with and without word and sentence stress (four combinations). Predictors in the LDA were the F1 and F2 of V1 and V2. Percentages of correct stress identification were 84 and 77 for words with and without sentence stress, respectively, and 68 and 71 for the reiterant non-words. These identification scores are better than chance (= 50%) but are poorer than what was observed for most other stress correlates (see below).

[+] Resistance to coarticulation

One characteristic of a spectrally expanded stressed syllable is that it shows minimal influence of coarticulation with abutting syllables, which in turn are strongly influenced by the adjacent stressed syllable. So properties of the stressed syllable are anticipated in the preceding syllable, and persevere into the following syllable, but the stressed syllable itself is hardly influenced by the abutting unstressed syllables. Resistance to coarticulation was claimed to be the most important correlate of stress in Lithuanian by Dogil (1999); see also Pakerys (1982, 1987).

One way in which the mutual coarticulatory influence of abutting syllables can be quantified would be to locate the beginning and end of vowel-onto-vowel formant transitions (if the formants do not move in synchrony, study the behaviour of F2 only) from the preceding syllable into the stressed syllable, and from the stressed into the following syllable (cf. Öhman 1967). Then determine the point along the time axis where half of the formant trajectory (i.e. half of the F2 frequency difference between the consecutive vowels) from the stressed to the unstressed vowel (and vice versa) has been covered. The coarticulatory window of the stressed syllable is then expressed as the time interval between the preceding and following 50% points divided by the duration of the stressed syllable. The larger the relative window size, the more resistant the syllable is to coarticulation.

[+] Acoustic correlates of sentence stress

Theories have been proposed in which there is no principled difference between word and sentence stress. In such views, e.g. in American structuralism (Bloch & Trager (1942) and early generative phonology (Chomsky & Halle (1968), Halle & Keyser (1971), sentence stresses were seen as merely stronger degrees of stress along a continuum, where degrees of stress differ along all stress-related acoustic parameters in proportion. More recently, phonetic research has brought to light, however, that sentence stresses – used to place constituents in focus – are marked in a principally different way than just word stresses. Typically, as long as there is no sentence stress on a word, the speaker makes no effort to change the vocal pitch. To be true, there may well be a small rise-fall contour on any vowel (with or without word stress) but this is due to an involuntary response of the glottal mechanism to the greater transglottal pressure that comes about when the oral tract opens during the articulation of the vowel sound; during the articulation of consonants the oral tract is fully or partially closed so that increased intraoral impedance reduces the transglottal pressure drop causing the vocal folds to vibrate more slowly. It has been estimated that the involuntary effect of mouth opening on the rate of vocal fold vibration does not normally exceed a threshold of 4 semitones (a frequency rise and subsequent fall of less than 25 percent). Only when a word is produced with sentence stress does the speaker issue a voluntary command to the glottal muscles that brings about a change in vocal pitch that (greatly) exceeds the 4-semitone threshold. Listeners intuitively know that small changes in vocal pitch require no planned action on the part of the speaker and therefore ignore these as a stress cue.

For a pitch change to impart sentence stress on a syllable the change has to be strictly local, i.e. has to take place within a time window that does not exceed the duration of a syllable. Gradual pitch movements (rises or falls that span a sequence of syllables) can never be prominence-lending (Hart, Collier & Cohen 1990). Yet, not any large and fast change in vocal pitch is associated with sentence stress. Fast pitch changes may also be used to mark prosodic boundaries. The difference between prominence-lending and boundary-marking pitch changes is in their timing relative to the segmental structure of the syllable. In Dutch, for instance, an equally large and fast pitch rise located in the first half of a syllable imparts prominence (sentence stress) but it marks the syllable as domain-final (intonation domain boundary or question marker) rather than stressed when executed in the final portion of the syllable (end of rise aligned to end of voicing). The phonetic details of the segmental alignments are quite subtle. Pitch movements or the component L and H targets may be synchronised (anchored) to segmental landmarks or with respect to each other (Caspers & Van Heuven 1993; Ladd et al. 1999; Ladd et al. 2000), the synchronisation may be affected by phonological properties of the (stressed) syllable (Dilley et al. 2005) and differ across languages (e.g. Arvaniti et al. 1998 for Greek versus Ladd et al. 2000 for Dutch) and even across dialects within a single language (e.g. Van Leyden & Van Heuven 2006).

Data collected by Sluijter & Van Heuven (1996) (see also Sluijter 1995: 106-116 for a more extended report) illustrate the point. Three male and three female speakers of American English each recorded two tokens of four minimal stress pairs (the noun-verb pairs export, uplift, digest and compact) as well as their reiterant versions with syllables /bi/, [bE], [bA] medially in fixed carrier sentences such that targets received either sentence stress or not. The F0 peak location was determined in each token as well as the excursion size of the F0 movement (in semitones). The size of the F0 change under sentence stress was two to three times larger (in semitones) than in items with word stress only. Most of the F0 movements associated with word stress only were below 4 semitones. When the token was produced with sentence stress it was nearly always the case that the F0 peak fell within the confines of the stressed syllable (in fact, without a single exception for the words) affording perfect identification of stress pattern in the four lexical pairs and near perfect stress identification in the reiterant versions (98% correct). However, when the tokens were produced with word stress only (and with a sentence stress on the phrase-final word), the location of the F0 peak was distributed more evenly over the two syllables and was aligned with the stress in only 65% of the cases (chance = 50%).

Secondary correlates of Dutch sentence stress can be found in temporal organisation. It has been shown for Dutch that words with sentence stress are lengthened by some 10 to 15 percent. Interestingly, all segments – whether stressed or not – in the word are lengthened to the same extent. The lengthening is restricted to only the word that carries the sentence stress; no lengthening spills over to adjacent words even if these are within the focus domain headed by the target – indicating that the lengthening is a correlate of sentence stress rather than of focus (Eefting 1991; Van Heuven 1998). Languages appear to differ in the domain they use for lengthening under sentence stress. It has been found for English that this domain is the within-word foot (excluding pre-stress syllables from the lengthening domain) rather than the (morpho-syntactic) word (Turk & Sawush 1997).

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Van Heuven (1993) made a further attempt to ascertain whether the lengthening effect in Dutch would extend to compounds or would be confined by the word boundary inside the compound. The results were inconclusive. This is still an area for further research.

[+] Relative strength of stress correlates

The relative strength of acoustic correlates of stress (or of any other linguistic distinction) can be estimated by applying some technique to compute effect size (see above). However, when the statistical distributions of acoustic correlates differ between samples, as they do in our case when correlates are measured for a sample of words with initial stress and a second sample of the stress partners with final stress (i.e. members of minimal stress pairs), more complex techniques are called for. It is expedient to use the LDA automatic classification algorithm as an estimator of effect size. The number of (above chance) classification errors would then serve as a good approximation of the relative strength of an acoustic correlate of stress. Normally, LDA uses multiple predictors to classify objects in categories. So, it seems tempting at first sight to have the algorithm make its classification with all measured acoustic correlates of stress in one run. This, however, defeats the purpose of the exercise. The acoustic properties of stress are generally correlated, some moderately, others more strongly. The LDA removes the shared variance from all but the most successful predictor, so that we will not get a true view of the effect size of the less successful predictors. Therefore, we routinely run the LDA with single predictors, repeating the procedure as many times as there are predictors. Only in this way can the percentages of successful classification be meaningfully compared. It is also necessary to instruct the LDA to assume equal probabilities for the two categories it has to predict (stressed, unstressed) rather than to compute a priori probabilities from the actual frequencies in the input data.

Sluijter & Van Heuven (1996) applied the LDA to the classification of initial and final stressed members of reiterant minimal stress pairs produced with and without sentence stress by six native speakers of American English (see Extra below). Analyses were run separately for word stress (targets outside focus) and sentence stress (targets in focus). Predictors were in both conditions:

  • the location of the F0 peak (in first or second syllable),
  • relative duration of the first syllable,
  • difference in peak intensity between the syllables,
  • the difference in Euclidean distance of the vowel from the centre of the formant space, and
  • the difference between the two syllables in five glottal parameters:  

  1. B1 (an estimate of completeness glottal closure),
  2. estimated tilt of source spectrum based on fundamental and amplitude of F2,
  3. tilt base on difference between fundamental and amplitude of F3,
  4. difference in Open Quotient (OQ estimated by the difference in amplitude between fundamental and second harmonic), and
  5. difference in amplitude of voicing (= amplitude of fundamental).

F0, duration and intensity yielded a very good classification of stress pattern for sentence stress (above 95% correct), vowel quality yielded only a 80% correct classification. The estimated glottal source parameters afforded between a 69 and 79% correct classification (the latter for spectral tilt between fundamental and F2), with an exception of amplitude of the fundamental, which yielded 97% correct and was in fact slightly better as a predictor than just overall peak intensity). Much poorer classification was obtained for word stress (in words out of focus). Location of the F0 peak, intensity, OQ and amplitude of fundamental were all between 60 and 65% correct (chance = 50%). B1 and the two tilt measures were at 75% correct. The best classification was given by duration and vowel quality (both at 80%).

A provisional conclusion from this comparison of parameter strengths would be that the difference between initial and final stress is more clearly marked in English when it is a matter of sentence stress than when we are dealing with just word stress. The effect sizes of the parameters differ substantially between sentence stress and word stress. The location of the F0 peak, peak intensity and amplitude of the fundamental are strong correlates in the sentence stress condition but not for word stress. Duration is a reliable correlate in both conditions, and so is spectral quality – be it less reliable than duration. The spectral tilt measures are only moderately successful correlates.

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See also Sluijter (1995: chapter 6) for a more detailed report of this study.

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