Recently, Roon, Hoole, Zeroual, Du, and Gafos (
In the past three decades, a number of parameters have been identified to affect inter-segmental overlap in C1C2 clusters. These include cluster position within a word (
Browman and Goldstein (
The conjectured link between overlap and some notion of rapidity by Browman and Goldstein (
Schematic representation of Jun’s proposal about the relationship between rapidity and overlap (recreated from
Recently, Roon et al. (
(1)
Ordering of rapidity:
Secondly, the rapidity ordering in (1) yields a further prediction in the form of a partial ordering in overlap between different cluster types shown in (2):
(2)
Partial ordering of overlap:
Roon et al. (
In assessing the effects of either of these two operationalizations of rapidity on overlap, Roon et al. (
Even though Roon et al. (
Finally, whereas much of the literature on consonantal overlap tends to retain an articulatory perspective, there is evidence that the generalizations at play may have a perceptuomotor rather than a purely articulatory basis (see, for instance, the proposed basis for the place order effect in
Here, we present the two broad hypotheses this work intends to assess. The first broad hypothesis posits that the observations and conclusions drawn by Roon et al. (
(3)
Results of Roon et al. (
• Component 1: There are no systematic differences in rapidity among
• Component 2: There is no rapidity-based difference in overlap between labial-lateral clusters and velar-lateral.
• Component 3: Overlap varies as a function of stiffness difference, rather than peak velocity difference, between C1 and C2.
Our second hypothesis aims to tease apart the separate contributions of C1 and C2 individual stiffness values on overlap. This hypothesis, stated in (4) below, was not assessed in Roon et al. (
(4)
Overlap in a cluster increases as the stiffness of C1 increases and that of C2 decreases.
If Jun’s schemas about the relations between the rapidities of C1 and C2 (interpreted in the present work by using stiffness rather than peak velocity) and overlap (that overlap increases as C1 rapidity increases and C2 rapidity decreases; see
Note that the approach in Jun (
The data analyzed in the present work are all subsets of articulatory data collected in previous experiments at the authors’ institution. The German dataset consists in recordings from six adult German native speakers. The speakers were all between 20 and 33 years old. The data in the English dataset derive from six adult American English native speakers. The Spanish articulatory data were collected from five native speakers of Standard Peninsular Spanish, all of which were between 18- and 35-years-old. No participants in any of these studies reported any hearing or speech problems. The experimental procedures were approved by the Ethics Committee at the authors’ institution. All the participants offered their informed consent to take part in the respective study and granted permission for publishing their anonymous data afterwards. Upon finishing the experiment, they were paid for their participation.
The German stimuli, shown in
Stimuli for all three languages. All clusters were word-initial.
Cluster | /bl/ | /pl/ | /gl/ | /kl/ |
---|---|---|---|---|
German | ||||
English | / | |||
Spanish | ||||
The English dataset, shown in
The Spanish stimuli, shown in
The word-initial clusters in German, English, and Spanish stimuli are all in primary-stressed syllables except for the /bl/ cluster in the English stimulus “blockade,” which has primary stress on the second syllable.
The German and Spanish articulatory data were registered using a Carstens AG501 three-dimensional Electromagnetic Articulograph (EMA) in the phonetics lab at the authors’ institution. Three sensors were attached along the midsagittal line of the tongue on its upper surface: a tongue tip sensor (TT) located approximately 1 cm posterior to the actual apex of the tongue, a tongue mid sensor (TM) located 2 cm posterior to the tongue tip sensor, followed by a tongue back sensor (TB) located 2 cm posterior to the tongue mid sensor. Three additional sensors were attached to the upper and lower lips and the jaw respectively. Reference sensors were placed on the upper incisor, behind the two ears on the left and right mastoid, and on the nose bridge to record the head movement. Three sensors were placed on a triangular bite place, which was held by the subjects between the upper and lower teeth to obtain a reference for the occlusal plane. Finally, the subjects were instructed to trace the shape of their hard palate using a sensor attached to the tip of their thumb. The data of the reference sensors were filtered using a cut-off frequency of 5 Hz, while the rest of the sensors’ data were filtered using a cut-off frequency of 20 Hz. During the recording, participants were instructed to read out phrases appearing on a computer screen located roughly one meter in front of them at a comfortable rate. The phrases were prompted by a separate computer outside the sound-proof booth, which also triggers the EMA system to start the recording. The kinematic movements of the sensors were recorded at a sampling rate of 250 Hz. Simultaneously, the acoustic data were also captured by a t.bone EM 9600 unidirectional microphone at a sampling rate of 48 kHz. After the recording was finished, data were corrected by subtracting the head movement captured by the reference sensors from the movement of all the other sensors. Last but not the least, the data were rotated for each subject based on their occlusal plane accordingly. The English corpus was acquired by the Northern Digital Inc. (NDI) Wave System. The same number of sensors was used for the English data collection as for the other datasets, and they were placed similarly to those used in the German and Spanish experiments. Articulatory data were recorded at a sampling rate of 400 Hz. Acoustic data were simultaneously acquired using the Schöps Colette modular system of microphones at a sampling rate of 25.6 kHz. For the reference sensors, the filter cut-off frequency was 5 Hz, while for all the other sensors it was 20 Hz. The raw data were processed by removing the contributions of head movement from the kinematic data of all the other sensors as well.
Articulatory segmentation denotes the process of identifying the timepoints, or temporal landmarks, at which the unfolding of an articulatory gesture for a consonant moves from one characteristic phase of movement to another. Hence, we need to first determine the correspondence between gestures and consonants. For each consonant in the word-initial clusters, its articulatory gesture was indexed by the movement of its primary oral articulator involved in its production. Thus, in all three languages the velar stops /g/ and /k/ were measured using the most posterior tongue back (TB) sensor; the labial stops /b/ and /p/ were measured using the lip aperture (LA) representing the distance between the upper and lower lips; and the alveolar lateral /l/ was measured using the tongue tip (TT) sensor.
The temporal landmarks of each gesture were identified automatically using the Matlab-based algorithm Mview developed at Haskins Laboratories by Mark Tiede. The user first selects a particular temporal range of interest in the entire recorded trajectory of a certain sensor corresponding to the movement of the main articulator for the intended gesture, and then applies the gesture identification algorithm within that window.
Temporal landmarks labeled by the Mview algorithm on the tongue body (TB) and tongue tip (TT) gestures of the word-initial /kl/ in the German word
Following Roon et al. (
However, the peak velocity of a movement is well-known to covary with the spatial excursion or amplitude of the movement (
(5)
Amplitude-normalized peak velocity:
This ratio of peak velocity to amplitude, which we denote as
Using the two measures of rapidity above, peak velocity and amplitude-normalized peak velocity, Roon et al. (
(6)
Peak velocity difference =
(7)
Stiffness difference =
Going beyond the assessment in Roon et al. (
To assess the robustness of the different presumed predictors of overlap, three different indices of articulatory overlap were used: relative overlap, onset lag, and absolute overlap. The former two were inherited from Roon et al. (
(8)
Relative overlap = 1 – (OnsetC2 – TargetC1) / (ReleaseC1 – TargetC1)
which can be further simplified into (9):
(9)
Relative overlap = ReleaseC1 – OnsetC2 / (ReleaseC1 – TargetC1)
By subtracting the timestamp of C2 onset from that of C1 release and then dividing by the duration of C1 plateau, relative overlap provides a way to quantify how early C2 movement is initiated within the constriction plateau of C1, while at the same time normalizing the lag between the release of C1 constriction and the onset of C2 by the plateau duration of C1 to account for speech rate variance. Therefore, higher values of relative overlap indicate that C2 starts early during C1 plateau, thus showing more overlap between the two consonants, whereas lower values indicate the opposite.
Indication of different values of relative overlap.
C2 Onset position |
Relative overlap value | Indication |
---|---|---|
A | > 1 | C2 onset before C1 plateau |
B | = 1 | C2 onset coincides with C1 onset |
C | (0, 1) | C2 onset during C1 plateau |
D | = 0 | C2 onset coincides with C1 release |
E | < 0 | C2 onset after C1 release |
As pointed out by Roon et al. (
Relative overlap reflects both the effect of rapidity and that of C1 plateau duration. Therefore, onset lag is used as a compensatory measure of overlap.
To compensate for this potential drawback of the measure of relative overlap and assess the robustness of different notions of rapidity as predictors of overlap, we followed Roon et al. (
Indication of different values of onset lag.
C2 Onset position | Onset Lag value | Indication |
---|---|---|
A | > 0 | C2 onset before C1 onset |
B | = 0 | C2 onset coincides with C1 onset |
C | < 0 | C2 onset after C1 onset |
(10)
Onset lag = OnsetC1 – OnsetC2
In addition to the two measures of overlap employed in Roon et al. (
(11)
Absolute overlap = ReleaseC1 – OnsetC2
In total, 658 German, 318 English, and 511 Spanish tokens were selected for the current study.
Indication of different values of absolute overlap.
C2 Onset position | Onset Lag value | Indication |
---|---|---|
A | > 0 | C2 onset before C1 release |
B | = 0 | C2 onset coincides with C1 release |
C | < 0 | C2 onset after C1 release |
Number of tokens for the analyses by language and cluster.
Cluster | /bl/ | /pl/ | /gl/ | /kl/ |
---|---|---|---|---|
German | 155 | 157 | 142 | 157 |
English | 38 | 156 | / | 124 |
Spanish | 163 | 122 | 104 | 91 |
Our aim here is to assess whether the findings of Roon et al. (
First, we looked at whether the notion of inherent velocity finds any basis in our data and specifically whether inherent velocities follow the order in (1),
Peak velocity (A) and stiffness (B) values, by primary articulator and cluster position in our German, English and Spanish datasets.
To determine which differences shown in the figures were significant, two linear mixed-effects models (
Results of the linear mixed-effect models evaluating differences in peak velocity (left) and stiffness (right) by articulator (Art.) for each language. Significant effects are in bold.
Peak velocity ( |
Stiffness ( |
||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Effect | df | Sum Sq | Mean Sq | Den. df | Sum Sq | Mean Sq | Den. df | ||||
Art. | 3 | 338 | 113 | 4.95 | 4.15 | 0.081 | |||||
Art. | 3 | ||||||||||
Art. | 3 | ||||||||||
There were significant effects of articulator across languages for peak velocity and significant effects of articulator in English and Spanish for stiffness. Post-hoc differences in articulator pairs within language were assessed using estimated marginal means (
Pairwise comparisons of estimated marginal means for articulators within language with movement rapidity indexed by peak velocity (left) and stiffness (right). Significant effects are in bold.
Peak Velocity ( |
Stiffness ( |
|||||||||
---|---|---|---|---|---|---|---|---|---|---|
Contrast | est. | est. | ||||||||
–1.73 | 1.14 | 5.00 | –1.51 | 0.494 | ||||||
3.06 | 1.47 | 5.00 | 2.08 | 0.276 | –4.38 | 1.72 | 5.00 | –2.54 | 0.167 | |
2.33 | 1.04 | 5.00 | 2.25 | 0.230 | –3.49 | 2.01 | 5.00 | –1.73 | 0.398 | |
–2.65 | 2.07 | 5.00 | –1.28 | 0.609 | ||||||
–1.76 | 1.62 | 5.00 | –1.08 | 0.715 | ||||||
–0.73 | 0.75 | 4.99 | –0.96 | 0.776 | 0.90 | 1.54 | 5.00 | 0.58 | 0.934 | |
–1.71 | 2.32 | 5.00 | –0.74 | 0.880 | ||||||
5.09 | 2.29 | 5.00 | 2.22 | 0.238 | ||||||
–2.96 | 0.97 | 4.93 | –3.06 | 0.097 | ||||||
–2.16 | 1.20 | 5.00 | –1.80 | 0.372 | ||||||
–0.87 | 1.65 | 5.00 | –0.53 | 0.948 | 0.81 | 1.22 | 4.97 | 0.66 | 0.907 | |
–2.48 | 2.17 | 3.99 | –1.15 | 0.685 | ||||||
–3.14 | 1.08 | 3.92 | –2.91 | 0.138 | ||||||
4.30 | 2.28 | 3.99 | 1.88 | 0.361 | –1.61 | 1.79 | 3.98 | –0.90 | 0.807 | |
6.33 | 2.56 | 4.00 | 2.47 | 0.205 | –0.66 | 1.37 | 4.00 | –0.48 | 0.960 | |
2.03 | 0.94 | 3.87 | 2.16 | 0.280 | 0.95 | 0.98 | 3.88 | 0.97 | 0.772 | |
In German,
Next, we inspected whether there were robust differences in overlap between
Relative overlap (A), onset lag (B) and absolute overlap (C) by cluster (i.e., /bl/, /gl/, /pl/, /kl/) in our German, English and Spanish datasets.
Three linear mixed-effects models were fit to the dataset of each language individually with either relative overlap or onset lag as the dependent variable to determine the reliability of the differences. Cluster type and C1 voicing were modeled as fixed effects for all models with
Results of the linear mixed-effects models with cluster type as a predictor of relative overlap (upper left), onset lag (upper right) and absolute overlap (lower left) within language. Significant effects compared to
Relative Overlap ( |
Onset Lag ( |
Absolute Overlap ( |
|||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Contrast | est. | est. | est. | ||||||||||||
(Intercept) | 0.77 | 0.15 | 5.51 | 4.16 | 0.003 | –108.23 | 10.54 | 5.59 | –10.27 | 0.000 | 47.08 | 8.77 | 5.24 | 5.37 | 0.024 |
0.09 | 0.15 | 7.30 | 0.59 | 0.575 | –12.74 | 7.24 | 21.31 | –1.76 | 0.093 | 12.25 | 9.39 | 6.53 | 1.31 | 0.236 | |
C1 voicing | |||||||||||||||
10.69 | 8.81 | 602 | 1.21 | 0.226 | 6.76 | 6.48 | 598 | 1.04 | 0.297 | ||||||
(Intercept) | 0.87 | 0.28 | 5.31 | 3.13 | 0.024 | –79.13 | 10.95 | 5.10 | –7.23 | 0.001 | 30.97 | 9.78 | 5.15 | 3.17 | 0.024 |
–0.21 | 0.18 | 3.80 | –1.20 | 0.301 | –10.25 | 8.47 | 4.95 | –1.21 | 0.281 | –7.76 | 6.88 | 4.41 | –1.13 | 0.317 | |
C1 voicing | |||||||||||||||
(Intercept) | 1.44 | 0.27 | 4.04 | 5.34 | 0.006 | –59.99 | 10.74 | 4.04 | –5.59 | 0.005 | 42.50 | 5.96 | 4.11 | 7.13 | 0.002 |
C1 voicing | |||||||||||||||
Lastly but most importantly, we turned to the effects of relative rapidity, where Roon et al. (
Relationship between within-token C1-C2 relative rapidity and relative overlap (A), onset lag (B) and absolute overlap (C) across our German, English and Spanish datasets. In the left two columns of each plot (
Across languages, cluster types, and speakers, stiffness difference mostly showed a positive correlation with the three overlap indices (right two columns in
Results of the 18 (6 models by 3 languages) linear mixed-effects models assessing the relation between overlap and relative rapidity. For each language, 6 models were fitted, each model assessing the relation between one of the three overlap measures and one of the two relative rapidity measures. Significant effects are bolded.
Relative overlap ( |
Onset lag ( |
Absolute overlap ( |
|||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
effect | est. | est. | est. | ||||||||||||
PV Difference | |||||||||||||||
(Intercept) | 0.45 | 0.20 | 7.21 | 2.27 | 0.057 | –143.97 | 13.97 | 7.18 | –10.30 | 0.000 | 33.29 | 11.42 | 5.36 | 2.92 | 0.031 |
PV Diff. | 0.40 | 0.34 | 589.40 | 1.17 | 0.245 | ||||||||||
0.38 | 0.21 | 5.27 | 1.78 | 0.132 | 16.11 | 10.37 | 3.06 | 1.55 | 0.216 | 18.32 | 14.99 | 4.47 | 1.22 | 0.282 | |
PV Diff.: |
–0.02 | 0.01 | 364.36 | –1.52 | 0.129 | –0.17 | 0.73 | 334.73 | –0.23 | 0.815 | |||||
(Intercept) | 0.36 | 0.28 | 10.46 | 1.29 | 0.223 | 14.73 | 0.84 | 9.50 | 1.50 | 0.167 | |||||
PV Diff. | –0.03 | 0.02 | 252.75 | –1.72 | 0.087 | –0.17 | 0.48 | 276.71 | –0.35 | 0.727 | |||||
–0.35 | 0.38 | 11.89 | –0.93 | 0.371 | –12.35 | 14.46 | 11.62 | –0.85 | 0.410 | –13.74 | 12.54 | 11.63 | –1.10 | 0.295 | |
PV Diff.: |
–0.01 | 0.03 | 192.67 | –0.39 | 0.700 | –0.75 | 0.87 | 182.10 | –0.86 | 0.390 | –0.09 | 0.81 | 180.51 | –0.11 | 0.909 |
(Intercept) | 1.09 | 0.29 | 5.95 | 3.74 | 0.010 | –76.27 | 12.42 | 5.85 | –6.14 | 0.001 | 35.09 | 6.98 | 6.01 | 5.03 | 0.002 |
PV Diff. | 0.00 | 0.01 | 384.15 | 0.40 | 0.687 | 0.56 | 0.31 | 61.28 | 1.81 | 0.075 | –0.04 | 0.23 | 156.22 | –0.15 | 0.880 |
–0.55 | 0.28 | 22.63 | –1.98 | 0.060 | –1.65 | 7.07 | 32.46 | –0.23 | 0.817 | ||||||
PV Diff.: |
0.01 | 0.01 | 245.68 | 0.82 | 0.413 | –0.11 | 0.51 | 31.78 | –0.21 | 0.838 | |||||
Stiffness Difference | |||||||||||||||
effect | est. | est. | est. | ||||||||||||
(Intercept) | 0.74 | 0.12 | 2.16 | 6.12 | 0.021 | –107.95 | 9.74 | 5.36 | –11.08 | 0.000 | 42.78 | 8.83 | 2.42 | 4.85 | 0.027 |
Stiff. Diff. | |||||||||||||||
0.32 | 0.22 | 4.85 | 1.44 | 0.212 | 2.67 | 11.65 | 3.71 | 0.23 | 0.831 | 26.25 | 14.98 | 4.38 | 1.75 | 0.149 | |
Stiff. Diff.: |
–0.72 | 0.48 | 450.02 | –1.48 | 0.139 | 0.22 | 0.33 | 490.46 | 0.67 | 0.504 | |||||
(Intercept) | 0.34 | 0.22 | 8.88 | 1.58 | 0.150 | –99.07 | 8.27 | 9.14 | –11.98 | 0.000 | 13.41 | 7.68 | 8.82 | 1.75 | 0.115 |
Stiff. Diff. | |||||||||||||||
–0.13 | 0.29 | 9.45 | –0.44 | 0.671 | –3.75 | 9.92 | 9.47 | –0.38 | 0.714 | –5.58 | 9.10 | 9.37 | –0.61 | 0.554 | |
Stiff. Diff.: |
–0.01 | 0.01 | 286.99 | –1.06 | 0.292 | –0.05 | 0.35 | 285.79 | –0.14 | 0.886 | –0.60 | 0.35 | 285.67 | –1.73 | 0.084 |
(Intercept) | 1.16 | 0.30 | 6.28 | 3.92 | 0.007 | –70.66 | 11.64 | 7.55 | –6.07 | 0.000 | 36.34 | 8.28 | 5.61 | 4.39 | 0.005 |
Stiff. Diff. | |||||||||||||||
–13.67 | 9.23 | 7.61 | –1.50 | 0.174 | |||||||||||
Stiff. Diff.: |
–0.17 | 0.48 | 467.16 | –0.34 | 0.731 | ||||||||||
The statistical results confirmed that effects of stiffness difference on the three overlap indices were all significant across all three languages and both cluster types (
Overall, stiffness difference does appear as a more robust predictor of overlap than peak velocity difference across languages, consistent with the findings of Roon et al. (
While Roon et al. (
Relationship between C1 or C2 stiffness and relative overlap (A), onset lag (B) and absolute overlap (C) across our German, English and Spanish datasets. C1 stiffness is shown in the left two columns of each plot (
Results of the 9 linear mixed-effects models assessing the relation between overlap and individual stiffness effects on overlap. For each language, 3 models were fitted, each model assessing the relation between one of the three overlap measures and C1/C2 stiffness. Significant effects are bolded.
Relative overlap ( |
Onset lag ( |
Absolute overlap ( |
|||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
effect | est. | est. | est. | ||||||||||||
(Intercept) | 1.48 | 0.19 | 12.23 | 7.77 | 0.000 | –211.37 | 15.82 | 29.83 | –13.36 | 0.000 | 126.37 | 13.02 | 9.81 | 9.71 | 0.000 |
C1 Stiff. | 0.11 | 0.43 | 536.32 | 0.26 | 0.799 | ||||||||||
C2 Stiff. | |||||||||||||||
30.19 | 18.77 | 10.35 | 1.61 | 0.138 | |||||||||||
C1 Stiff.: |
–0.55 | 0.62 | 593.01 | –0.89 | 0.376 | ||||||||||
C2 Stiff.: |
–0.38 | 0.50 | 387.40 | –0.762 | 0.447 | –0.06 | 0.31 | 586.06 | –0.20 | 0.844 | |||||
(Intercept) | 1.38 | 0.44 | 115.03 | 3.13 | 0.000 | –105.23 | 14.23 | 65.76 | –7.40 | 0.000 | 45.31 | 13.36 | 79.40 | 3.39 | 0.001 |
C1 Stiff. | 0.03 | 0.02 | 265.89 | 1.81 | 0.071 | ||||||||||
C2 Stiff. | |||||||||||||||
0.36 | 0.75 | 174.13 | 0.47 | 0.636 | –0.12 | 21.83 | 159.38 | –0.01 | 0.996 | ||||||
C1 Stiff.: |
–0.05 | 0.04 | 273.27 | –1.44 | 0.151 | 1.94 | 1.03 | 270.38 | 1.90 | 0.059 | –1.29 | 1.00 | 276.93 | –1.28 | 0.202 |
C2 Stiff.: |
0.01 | 0.01 | 284.09 | 0.90 | 0.369 | 0.30 | 0.38 | 282.78 | 0.79 | 0.430 | 0.63 | 0.37 | 282.65 | 1.69 | 0.093 |
(Intercept) | 3.30 | 0.44 | 25.85 | 7.49 | 0.000 | –96.40 | 18.86 | 49.36 | –5.11 | 0.000 | 118.36 | 12.28 | 40.41 | 9.64 | 0.000 |
C1 Stiff. | –0.00 | 0.01 | 289.90 | –0.17 | 0.869 | –0.76 | 0.44 | 153.39 | –1.75 | 0.083 | |||||
C2 Stiff. | |||||||||||||||
–77.367 | 24.92 | 93.77 | –3.11 | 0.003 | –29.81 | 15.52 | 188.90 | –1.92 | 0.056 | ||||||
C1 Stiff.: |
–0.00 | 0.02 | 380.92 | –0.16 | 0.875 | 0.12 | 0.77 | 416.66 | 0.16 | 0.876 | 1.00 | 0.52 | 260.56 | 1.93 | 0.055 |
C2 Stiff.: |
–0.31 | 0.45 | 463.89 | –0.70 | 0.483 | ||||||||||
Statistical results provide evidence for C2 stiffness as a robust predictor of overlap, as its effect on overlap was significant across languages, cluster types, and overlap indices. The only exception was Spanish
In short, C2 stiffness is a more robust predictor of overlap compared to C1 stiffness for two reasons. Firstly, it has a significant effect on overlap across the three overlap measures and the three languages (only one exception out of 18 cluster type-and-overlap combinations). Secondly, the prediction of Hypothesis 2 on the effect direction of C2 stiffness (negative) was validated by the empirical results across languages and overlap indices, whereas that of C1 stiffness was not, given that significant effects of C1 stiffness had different effect directions for the
The findings of Roon et al. (
A first finding is that the rapidities of coronals, labials, and velars did not differ systematically and robustly from each other in stop-lateral clusters of German, English, and Spanish. This goes against the notion of an articulator-specific inherent velocity proposed by Browman and Goldstein (
Since significant differences in rapidity measures were not obtained for the three articulators across languages, there was no rapidity-difference basis on which to expect
The second finding of the current study, which is in line with Roon et al. (
A more realistic revision of the schemas in
The comparison intended by Jun (
Comparison between a C1C2 sequence with high C2 stiffness and another with low C2 stiffness when C1 is held constant.
Extending the investigation of Roon et al. (
This finding goes against the prediction implicit in Jun’s schemas given in
Relationship between C2 stiffness and the temporal interval from C2 onset to C1 release in German, English and Spanish word-initial /Cl/ clusters grouped up by cluster types (A) and clusters (B). Data points to the left versus right of the 0 on the x-axis represent instances of “late” versus “early” C2s, that is, instances where C2 onset occurs after versus before C1 release.
Placing our results in a broader context, let us note that the compensatory nature of the relation between onset of movement of C2 and its stiffness (the greater the overlap, or in other words, the earlier the initiation of C2 with respect to C1, the lower its stiffness; and vice versa) as reported in Gafos et al. (
To maintain some lag in time between C1 and C2 so as to ensure C1 perceptibility, the earlier C2 starts within C1 (compare Onset B to Onset A), the lower its stiffness (slower C2 rise to its target). Conversely, the later C2 starts within C1 (compare Onset C to Onset A), the higher its stiffness (faster C2 rise to its target).
The present study both confirms and extends earlier findings (
“Typically, the underlying gesture with which coronals are realized is articulated more rapidly. That is, tongue tip gestures are rapid and thus have rapid transition cues; whereas tongue dorsum and lip gestures are more sluggish and thus give rise to long transitions.’’ (
Jun’s argument for the relative saliency between the non-coronals is more nuanced and does not call on rapidity
Thus, for instance, stiffness as measured by the peak velocity to amplitude ratio has been implicated in spatio-temporal modulations at prosodic boundaries (
The letters ‘A, B, C, D, E’ refer to different C2 onset timestamps relative to the unfolding of C1, as further specified under the ‘Indication’ column, which in turn determines the quantitative range the value of relative overlap falls in. The same conventions apply to
The total number of tokens measured was 1541 (707 German, 318 English, 516 English). A first-pass automatic segmentation indicated that 54 from these tokens, deriving from the German datasets, had a C1 onset starting at least 250 ms earlier than C2 onset. Most of these tokens were produced in the German carrier phrases where an utterance boundary preceded C1,
One of the reviewers pointed out that Spanish
One reviewer noted that Spanish
Note that despite the significant interactions between stiffness difference and
Whence the apparent linearity of the relation in the Spanish subset? In Spanish C1C2 clusters, C2 onset occurs mostly earlier (datapoints to the right of the 0 on the x-axis) than C1 release, while in German and English clusters, C2 onset is distributed more freely to occur both earlier and later (datapoints to the left of the 0 on the x-axis) than C1 release. This more restricted range of datapoints results in squeezing the depicted relation to a flatter slope in the Spanish subset.
The authors thank Dr. Stavroula Sotiropoulou, Dr. Stephan R. Kuberski, and Dr. Manfred Pastätter for providing invaluable support in scripting and data processing. We also thank the members of the Phonology & Phonetics research group of the Linguistics Department at the University of Potsdam, who provided extensive feedback on the initial drafts of this study.
This work has been funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project ID 317633480 – SFB 1287, Project C04.
The authors have no competing interests to declare.
The authors contributed equally to this work.