Substantive bias in the learning of harmony patterns
Allison Shapp
New York University
December 5, 2012
1
Introduction
Not all possible linguistic patterns are learned with the same ease, and both effects of the
formal structure (analytic bias) and effects of the phonetic content (substantive bias) of
the patterns have been shown to exist. (Moreton 2008, Carpenter 2010). In regards to
the substantive content of phonological patterns, some patterns can be shown to be better
phonetically grounded than others. Often, phonetically grounded patterns are also widely
attested, but this is not always the case. The experiments in this paper compare anteriority
harmony, which is phonetically grounded and well attested, with voicing harmony, which
is less well grounded and also typologically rare. The results of these experiments show
that the anteriority harmony is better learned than the voicing harmony. In this case, the
learnability, phonetic grounding, and typological attestation of these two patterns are all in
line with each other. These two formally identical patterns differ only in the feature being
harmonized, yet one of them is easier to learn. This asymmetry supports a substantive bias
in learnability.
2
Previous Research on Learnability
The learnability of linguistic patterns, as well as analytic bias and substantive bias specifically, have been fruitfully explored through the use of artificial grammar learning experiments, where participants are taught linguistic patterns in a made-up language. Previous research has shown that phonological patterns can be successfully taught through this method,
and results which show both analytic and substantive bias have been found. Here I will summarize several of these previous results and use them to set the stage for the presentation
of my experiments. In section 2.1 I discuss learning studies more generally, then in 2.2 I
specifically look at a few studies that deal with substantive bias.
2.1
Learning Linguistic Patterns in Artificial Grammar
In Finley and Badecker (2009), English speakers were taught a backness vowel harmony
pattern. The stimuli were stems of the form CVCV with an additional -CV syllable as a
suffix. The suffix was either -mi if the C2 of the stem was a front vowel (/i/, /e/, or /æ/), and
-mu if the preceding vowel in the stem was back (/u/, /o/, or /a/). The method they used for
training the participants was an alternation. Participants were presented with a stem, such as
[p ædi] or [muto], and then stem+suffix pairs where the vowel in the suffix matched the vowel
1
in the stem on the feature of backness ([pædimi] or [mutomu], respectively). Participants
were part of either a mid-holdout group or a low-holdout group. The mid-holdout group
was trained on harmonic stimuli consisting of only high and low vowels, and the low-holdout
group was trained on only high and mid vowels. Then all participants were asked in a forced
choice test to choose between a harmonic suffixed form and a disharmonic suffixed form.
They were tested on old stems, new stems with the same consonant and vowel inventory
that they saw in training, and finally, new stems that contained the vowel class that they
were not exposed to during training.
Finley and Badecker found that participants were able to learn the vowel harmony and
generalize it to novel segments (those in the height class that they were not trained on),
suggesting that it was feature-based learning that was happening rather than segment level
learning. If the learning had been segment level, the participants would not have been able
to produce the same backness harmony for the vowel segments they had not been exposed
to in training. Finley and Badecker (2009) had very robust findings that this pattern was
learned well by their participants, and that feature based generalizations were being formed.
Finley (2011) ran a similar experiment, teaching a pattern of harmony of sibilant consonants. Participants were again given alternations of stem+suffix pairs, where if the last
consonant in the stem was a [S] then the suffix was [-Su], and if the last consonant in the
stem was [s], then the suffix was [-su]. Stimuli stems were only of the form CVsV or CVSV,
so the target consonant was always identical to the trigger consonant in harmonic stimuli.
In testing, participants were given a two-alternative forced-choice between a harmonic and a
disharmonic form that differed only between the two suffixes (e.g. [bisisu] vs. [bisiSu]), and
asked to choose which was part of the language that they just learned in training.
Finley’s results show that subjects favored harmonic forms more in the training condition
than in the control condition, but the experiment only tested cases of strict segmental identity
(only one anterior segment [s] and one posterior segment [S] were used). I test the same
anteriority harmony pattern in the experiments in this paper, but in both training and
testing there are three anterior segments [s,z,ts] and three posterior segments [S, Z, tS]. My
results show that anteriority harmony can be learned at the featural level among non-identical
segments.
Moreton (2008) investigated how well different assimilation patterns were learned based
on both analytic structures and different substantive structures. He isolates the effects of
analytic bias, as opposed to substantive bias, by choosing two patterns that are equally well
phonetically grounded but differ in formal representation. He looked at patterns where vowel
height matched vowel height (HH) and patterns where there was a dependency between vowel
height and consonant voicing (HV). Moreton identifies two phonetic precursors that make
HV patterns phonetically grounded: the tendency for vocalic articulations to be exaggerated
before voiceless obstruents, and the pharyngeal-cavity expansion which occurs during the
production of voiced obstruents (Thomas 2000). Both precursors lead to a slightly lower
vowel F1 before a voiceless obstruent than before a voiced one (Moreton 2008). Moreton did
a survey of studies that measured vowel F1 in the relevant contexts for HH and HV patterns,
and found the phonetic precursors of both types of patterns to be comparable in size.
In Moreton’s study, the two patterns, HH and HV, are typologically asymmetrical. In a
typological survey, Moreton found HH patterns to exist in many language families, but only
a few marginal cases of HV patterns were found. An example of an HV pattern is found in
Polish, where /O/ raises to [o] before underlyingly voiced non-nasal codas. The productivity
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of this pattern is doubtful, though (Sanders 2003).
Moreton then tested how well the two patterns, HH and HV, were learned in an artificial
grammar experiment. Moreton used phonotactic training rather than the alternation training
used by Finley (2010) and Finley and Badecker (2009). He trained the participants by having
them hear and produce a set of forms that conformed to the relevant phonotactic pattern.
All training stimuli had the form CVCV. Participants were trained on stimuli that exhibited
either HH harmony (/titu/, /titi/) or HV harmony (/tidO/, /tudæ/). They then heard novel
forms and had to decide if they were part of the language they had trained on. Moreton found
that the HH patterns were learned at higher rates than the HV pattern, despite the fact that
the two patterns are equally phonetically grounded. Moreton attributes this difference in
learnability to analytic bias based on the difference that HH patterns are agreement in the
same feature of the same type of segment, while HV patterns are assimilation of different
features between different segment types, one consonant and one vowel.
Moreton then conducted a second experiment that tested HV harmony against VoiceVoice (VV) harmony patterns. This comparison involves a substantive difference, because
the HV pattern is phonetically grounded while the VV pattern is not, as well as an analytic
difference, but both patterns are typologically rare. Moreton’s VV harmony is the same pattern that is used in the experiments described in this paper (see Section 3.1.2 for typological
examples). The stimuli were again CVCV and constructed from the same inventory. The
results of this second experiment showed that the VV patterns were learned better than the
HV patterns, but worse than the HH patterns from the first experiment.
2.2
Substantive Bias in Artificial Grammar Learning
The experiments in Carpenter (2010) are designed specifically to test substantive bias in the
learning of phonological patterns, by conducting an artificial grammar experiment teaching
two different stress patterns that were identical except for their phonetic grounding. Carpenter characterizes the following pattern as phonetically natural: stress leftmost low vowel,
else stress leftmost vowel. To create a formally similar but phonetically unnatural pattern,
she takes the opposite of her natural pattern: stress leftmost high vowel, else stress leftmost
vowel. The phonetic grounding of the natural pattern is based on the fact that when stress
is sensitive to vowel quality, it favors low vowels. Stress has been observed to seek high
sonority segments (de Lacy 2002), and low vowels are more sonorous than mid vowels, which
are more sonorous than high vowels (Clements 1990). Her two patterns are formally parallel
but differ in phonetic content, allowing the results of the experiment to isolate the effects of
substantive bias. Additionally, her natural pattern is rare but typologically attested, while
her unnatural pattern is completely unattested.
Participants were trained by listening to nonce words that exhibited the stress patter.
Then they were tested on choosing a correctly stressed word over an incorrectly stressed version of the same nonce word in a two-alternative forced-choice task. Carpenter’s participants
were both English speakers, a language with lexical stress, and French speakers, a language
with predictable stress. Carpenter added additional pre-training for French speaking participants in order to accommodate their “stress deafness” (Dupoux et al. 1997) and ensure
they were able to learn new stress patterns. Both English and French speakers learned the
phonetically grounded pattern significantly better than the ungrounded one, supporting the
involvement of a substantive bias in the learning of phonological patterns.
3
Wilson (2006) also aims to specifically test the effects of substantive bias in linguistic
pattern learning. In this experiment, participants were trained on a phonological pattern
and it was observed that they extended this pattern to novel contexts and sounds in ways
that accord with linguistic typology. Wilson taught a pattern of velar palatalization before
a vowel which was either a mid vowel or a high vowel. Velar stops preceding a vowel
are articulated further forward on the palate the further front the vowel is (Keating &
Lahiri 1993), making them more similar to palatoalveolar affricates before [i] than before
[e]. This difference in phonetic grounding between the two patterns that Wilson tested
correlates with linguistic typology in that palatalization before mid vowels asymmetrically
implies palatalization before high vowels in most attested languages. If participants were to
exhibit substantive bias in the learning of these patterns in the artificial grammar learning
experiment, they would be expected to generalize a pattern of palatalization before midvowels to high-vowels, but not the other way around.
The stimuli in this experiment were CVCV nonce words. Participants were asked to play
a language game where they were presented with two stimulus items, and then repeated the
second member of the pair in training. There were two experimental groups: participants
either were trained on velar palatalization only before mid-vowels (e.g. were given a pair
[ken@] [tSen@]) or only before high vowels (e.g. [gip@] [dZip@]). In testing, the participants
were asked to supply the second member of the pair themselves. In testing, the velar could
appear before any one of the vowels [i, e, A], but the participant would have only previously
encountered velarization in training before one of either [i] or [e].
Wilson’s results showed that participants in the high condition palatalized more often
before high vowels in testing than before mid and low vowels, and participants in the mid
condition palatalized equally often in all vocalic environments. Participants thus were able
to generalize a learned pattern of palatalization before a mid-vowel to palatalization before
a high vowel, but did not generalize from high to mid vowels. The generalizations go beyond
the training data, and they do so in a way that reflects the phonetic grounding of the
patterns. Wilson’s results thus support a substantive learning bias of the patterns.
The research summarized here has shown that participants in artificial grammar learning
settings can learn phonological patterns (Finley & Badecker 2009, Finley 2011). Research
has been done on what types of patterns can be learned and which are easier to learn than
others. It has been shown that patterns with certain analytic properties can be easier to
learn (Moreton 2008), and other research has identified different substantive patterns that
are better learned (Carpenter 2010, Wilson 2006). My experiments look at two patterns that
have not been looked at together closely before, anteriority harmony and voicing harmony.
These two patterns differ in phonetic content (only the feature being harmonized is different)
but are otherwise formally identical. Anteriority harmony has plausible phonetic grounding,
unlike voicing harmony. It is also widely typologically attested, whereas cases of voicing
harmony are rare or dubious. My results show that the anteriority harmony pattern was
learned better than the voicing harmony pattern, and thus support a substantive bias in the
learning of these patterns.
3
Anteriority vs. Voicing
In this section I lay out the typological attestation of anteriority harmony and voicing harmony, the two patterns that are compared in the experiments in this paper, and discuss their
4
phonetic grounding. Anteriority harmony is widely attested in the world’s languages, even
seen as the“prototypical” example of consonant harmony, while voicing harmony is very rare
and the few identified cases are marginal. The typological survey here is based on Hansson (2001)’s database documenting 120 languages with consonant harmony of various types.
Discussion of the phonetic grounding of the two patterns shows that anteriority harmony
across a vowel can be articulatory local, whereas voicelessness harmony cannot.
3.1
3.1.1
Typological Attestation
Anteriority Harmony
In Hansson’s database, coronal harmony is by far the most common type of harmony, and
Gafos (1996 [1999]) makes the even stronger claim that coronal harmony is the only possible
type of consonant harmony. Coronal harmony refers to assimilatory interactions between
coronals where the property involved is ‘minor place of articulation’ and has to do with the
configuration of the tongue tip and blade. Coronal harmony is attested for a wide range of
segment types including stops, affricates, fricatives, nasals, and liquids. The most common
type of coronal harmony is the one used in the below experiments, sibilant harmony.
Hansson calls sibilant harmony the“prototypical consonant harmony.” Sibilant harmony
systems make up about 1/3 of the entries in Hansson’s database, and the languages involved
belong to about 15 different language families distributed over four continents. The most
common contrast to participate in sibilant harmony is alveolar vs. post-alveolar, i.e. /s, z,
ts, dz/ vs. /S, Z, tS, dZ/.
Navajo sibilant harmony is one of the best known examples of consonant harmony. In
Navajo, sibilant harmony applies from right to left in an alternation involving prefixes and
roots. A sibilant in the root triggers assimilation to a target sibilant in the prefix, which will
then trigger assimilation in any additional preceding prefixes.
(1) Sibilant harmony in Navajo (data from McDonough 1991)
a. /j-iS-mas/
jismas
“I’m rolling along.”
b. /dz-iS-l-ta:l/
dZiSta:l
“I kick him [below the belt]”
Similar sibilant harmony can be found in other Southern Athapaskan languages (e.g.
Chiricahua Apache, Kiowa Apache), as well as in the Northern and Pacific Coast branches
of Athapaskan. Sibilant harmony as a root-internal cooccurrence restriction can be reconstructed as far back as Proto-Athapaskan-Eyak (Krauss 1964). In these languages, the
sibilant harmony is almost always anticipatory, occurring from right to left. In many cases
this is epiphenominal of the morphological structure. Sibilant harmony often occurs “inside
out,” or from the root to affixes, and the Athapaskan languages have primarily prefixing
morphology. Alveolar vs. post-alveolar sibilant harmony, both root-internal and involving
affixes, can also be found in many other native North American languages.
Sibilant harmony involving the alveolar vs. postalveolar distinction is also found in many
African languages. In the Afro-Asiatic family, it is independently attested in at least three
branches, and it also is found in various branches of the Niger-Congo family. The language
Koyra of the Omotic subgrouping of Afro-asiatic languages exhibits this harmony both root
internally as well as in alternation in affixes, where /s, z/ -> [S, Z].
5
(2) Harmony in Koyra Suffixes /-us/, /-os:o/, and /-es:e/
“cause to fear”
dZaS-uS
patS:-oS:o
“it became less”
dZaS-uS-eS:e
“let him/them frighten (s.o.)!”
In both the root internal and alternation examples of the sibilant harmony pattern in
Koyra, the two consonants can be separated by at most a vowel; harmony does not hold at
greater distances:
(3)
Sod-us
Sod:-os:o
“cause to uproot”
“he uprooted”
(*Sod-uS)
(*Sodd-oS:o)
But in other languages like Aari and Gimira there is no limit on the distances between
the trigger and the target consonants in sibilant harmony. (Hayward 1988, Breeze 1990).
‘Coronal harmony’ refers to interactions that involve ‘minor place of articulation’ of the
tongue tip and blade. Parameters that can be contrasted include tongue posture (apical vs.
laminal) and target region (dental vs. alveolar vs. postalveolar) (Hansson 2001). Several
combinations of these contrasts are attested in languages, including lamino-dental vs. alveolar, retroflex vs. lamino- alveolar, alveolar vs. retroflex, and alveolar vs. lamino-postalveolar.
Three-way anteriority contrasts also exist, with, for example dental vs. alveolar vs. postalveolar.
Anteriority harmony, especially harmony in the alveolar vs. postalveolar distinction, is
thus robustly attested in the world’s languages. It is independently attested in many different language families in different parts of the world, and makes up a large portion of all
cases of consonant harmony in Hansson’s database.
3.1.2
Voicing Harmony
While harmony of laryngeal features is relatively well attested, most of the cases involve
pulmonic vs. glottalic distinctions, while very few involve voicing. In addition, laryngeal
harmony where it does exist rarely extends across morpheme boundaries, so it is not involved in alternations. It most commonly manifests itself as a static root-level cooccurrence
restriction, such as in Ngizim, the one solid example of voicing harmony in Hansson (2001).
Hansson cites only two cases of laryngeal harmony resulting in alternations and they are both
voicing harmony, Yabem (Oceanic) and Kera, but both these cases turn out to be suspect.
In Ngizim, a West Chadic language, obstruents in a root are either both voiced or both
voiceless. The harmony is not sensitive to differences in stricture, so fricatives and stops are
both affected.
(4) Root-level laryngeal harmony in Ngizim (data from Schuh 1997)
kùt´@r
“tail”
tàsáu
“find”
d´@bâ
“woven tray”
z`@dù
“six”
6
The restriction in Ngizim is asymmetric in two ways, in that it is strictly anticipatory,
applying only from right to left, and it does not cause voiced obstruents to ever become
voiceless. Thus, examples with the form D...T exist, but not *T...D.
(5) Asymmetric character of Ngizim voicing harmony (data from Schuh 1997)
“roast”
bàkú
gùmtSí
“chin”
Yabem and Kera are the two languages given as examples by Hansson (2001) of laryngeal
harmony in alternation, but both are disputed as actual cases of voicing harmony. Yabem
is an Austronesian language of Papua New Guinea (Dempwolff 1939). In Yabem, tone and
voicing are directly correlated in obstruents: in high-toned syllables, stops are voiceless,
whereas in low-toned syllables, they are voiced. This is illustrated in the following minimal
pairs:
(6) a. minimal pair without obstruents
áwé
“outside”
àwè
“woman”
b. minimal pair containing obstruents
típ
“shell”
dìb
“speech”
In Yabem, when a prefix containing an obstruent combines with a root containing obstruents, the obstruents agree in voicing, but whether they are all voiced or all voiceless depends
on the tone in the root. For example:
(7) 1st Sg prefix /ka-/
a. Before high-toned root:
ká-táN
“I weep” (realis)
b. Before low-toned root:
gà-dèN
“I move towards” (realis)
However, this only holds with monosyllabic roots. Looking only at voicing, it would
appear the cooccurrence restriction is enforced only within a word final foot, and does not
reach across foot boundaries. Hansson concludes that there is no need to describe this pattern
in Yabem as voicing harmony at all. Since obstruent voicing is completely predicable based
on tone, the facts in Yabem could be described as exhibiting foot-bounded tone harmony
instead. This is a preferable analysis because tone spread and tonal harmony are well-attested
phenomena (Goldsmith 1976).
In Kera, if a root contains a plosive stop or affricate, then plosives in any affix (both
prefixes and suffixes) will agree in voicing with the root plosive.
(8) Laryngeal harmony alternations in Kera (Ebert 1979)
a. nominal prefix /k-/
“cooking pot (plur.)”
k@-taatá-w
g@-dàar`@
“friend”
7
b. feminine suffix /-ka/
“black (fem.)”
sár-ká
dZàr-gá
“colorful (fem.)”
The laryngeal harmony in Kera is parasitic on identity in stricture, i.e. plosive voicing
does not interact with the voicing of fricatives or sonorants. The harmony thus can be nonlocal across a vowel or other segment that does not participate in the harmony. The voicing
harmony in Kera is asymmetric in that voiceless plosives become voiced but voiced plosives
will not become voiceless.
Pearce (2006) gives evidence against this pattern in Kera being voicing spread at all. She
presents exceptions to the voicing agreement, and argues that the data can be accounted
for by tone spreading and the resultant change in VOT. In a statistical analysis of a lexicon
constructed from her corpus of collected Kera speech, Pearce finds that 9% of all words in
the lexicon have a voicing mismatch. She gives examples such as the following:
(9) Kera nominal prefix /k-/
k-ágày
“hoe (plur.)”
k-ágàmlà
“bull (plur.)”
The words in (9) have voiced obstruents in their roots, so the voicing spread account
predicts that the prefixes should also be voiced, as seen in (8a). However, a tone-spreading
account would predict that since the first syllable in the root has a high tone, the prefix
as the onset of that syllable will have long VOT, making it perceived as voiceless. The
facts in (9) support the second account, the explanation of tone spreading rather than voice
spreading.
Thus, there are very few cases of voicing harmony attested in the world’s languages.
Ngizim is the only example Hansson gives that remains considered a voicing harmony pattern.
It only applies to voiceless consonants becoming voiced and is also strictly anticipatory, while
there are several cases of anteriority harmony that are totally symmetric and exceptionless.
It is clear that while anteriority harmony is extremely robustly attested, cases of voicing
harmony are vanishingly rare.
3.2
Phonetic Grounding
While phonological grammar carries out formal manipulations of abstract symbols, phonetics
is grounded in human capabilities for speech production and speech perception. Evaluating
phonological concepts based on facts about the physical world gives us an idea of the phonetic grounding of a given phonological pattern. Depending on the phonological theory (for
example, taking a feature matching view of harmony), the patterns of anteriority harmony
and voicing harmony may be formally identical and a difference in their implementation
would not be expected. However, anteriority and voicing are not the same with regards to
physical production in the vocal tract, and so they are not both phonetically grounded to
the same extent.
For a pattern to be consonant harmony, at minimum, an intervening vowel must be
present and must not be audibly affected by the assimilating feature. How this is possible
for anteriority harmony is clear. Anteriority is articulated using the tongue tip and blade,
and this gesture can be carried through a vowel without changing its perception. In the
following figure, representing a simplified gestural representation of the utterance [sas], the
8
tongue tip can have a constriction location of alveolar throughout the utterance, because
this gesture does not affect the percept of the vowel. If the utterance were [SaS], then the
constriction location of the tongue tip would be postalveolar, but the concept would be the
same
Figure 1: Simplified gestural score of an example of anteriority harmony
Gafos (1996 [1999])’s theory of articulatory locality says that consonant harmony can
only involve articulatory specifications controlling the shape of and orientation of the tongue
tip and blade, since only those can pass through intervening vowels and consonants without
interfering with their acoustic properties or articulation. In Gafos’ view, all harmony is
driven by the desire to minimize the number of gestures required to produce an utterance.
Thus, Gafos predicts that coronal harmony with distinctions such as dental vs. alveolar,
alveolar vs. postalveolar, and apical vs. laminal, is the only type of consonant harmony
possible at all.
It is impossible, however, to produce an output such as [pap], with voiceless consonants on
either side of a voiced vowel, with only one gesture producing the voicing values. Voicing is
represented by opening and closing gestures of the glottis. At the beginning of the utterance,
the glottis is open, and then from /p/ to /a/ the glottis closes. From /a/ to the second /p/
there is a second opening gesture of the glottis. In this case one gesture cannot be held
through the whole utterance without affecting the percept of the vowel.
Figure 2: Simplified gestural score of an example of voicing harmony
The main difference between the articulation of patterns like those in Figure 1 and Figure
2, is that it is possible to produce anteriority harmony with one gesture across a vowel, but it
9
is necessary to have two separate opening gestures of the glottis to produce the utterance with
harmony of [−voice]. In this way, anteriority harmony minimizes the number of articulatory
gestures necessary and thus is more phonetically motivated than a voicing harmony pattern,
which requires more gestures.
4
The Experiments
In this section I will describe the artificial grammar learning experiments that were conducted
to test and compare the learnability of anteriority harmony and voicing harmony. Then
I will present and discuss the results of the experiments. The two experiments exposed
adult learners to an artificial language exhibiting a consonant harmony pattern involving
harmony in either voicing or anteriority. I used the alternation training method of Finley
and Badecker (2009) because it has yielded stronger effect sizes in past research than has
phonotactic training like that in Moreton’s (2008) experiments. Participants were then tested
on whether they had learned this pattern.
4.1
Stimuli
The stimuli were stem items with the structure CVCV that each had 2 corresponding suffixed
forms with the structure CVCVCV. All stimuli were nonce words created by combining a
set of 3 consonants in the C1 slot and 6 consonants in the C2 slot, with 4 vowel patterns.
C1 and C2 were never identical, and V1 and V2 were never identical. There was a total of
72 stems that could take each of 2 different suffixes, resulting in 216 total stimulus items for
each experiment.
For the anteriority experiment, the C2 , or trigger of the harmony in the suffix, was one
of 6 sibilants: 3 anterior sibilants [s, z, ts] and 3 posterior sibilants [S, Z, tS]. The C1 in
all items was outside the harmony paradigm, meaning they were chosen so as not to have
a counterpart in English phonology that would exhibit the feature contrast salient to the
harmony being tested. C1 s for the anteriority experiment were voiceless stops: [p,t,k]. The
suffix was either -sa or -Sa. The stimuli were thus items like [pasi], which when suffixed would
be [pasisa], or [tiSu] which would be [tiSuSa] when given a harmonic suffix.
For the voicing experiment, C2 was one of 6 stops: 3 voiced stops [b, d, g] and 3 voiceless
stops [p,t,k]. The C1 for the voicing experiment was one of [m, n, l]. The suffix was either
-pa or -ba. Both experiments used the vowels [a, i, o, u] in four configurations so that each
vowel was V1 and V2 in one configuration. These vowel patterns were: [a, i], [i, u], [o, a],
and [u, o]. Stimuli for the voicing experiment were thus items like [madi] which when given
a harmonic suffix would be [madiba], or [laki] which would become [lakipa] when suffixed
harmonically.
Each experiment also had 24 filler stems that also took both applicable suffixes for the
paradigm. The fillers for both experiments used the same 4 vowel configurations and C1
consonants as the experimental stimuli, but the C2 were replaced with consonants that could
not participate in the relevant harmony. The anteriority experiment fillers used [p,t,k,m,n,l]
as C2 , producing filler stems like [pami] and [toka]. The voicing fillers used [m, n, l, w, j] for
C2 , producing filler stems such as [nali] and [mowa].
All stimuli were recorded in a sound booth on a Zoom H4 recorder, by a native Hebrew
speaker who was unaware of the purpose of the experiment. A Hebrew speaker was chosen
10
Posterior Trigger
Anterior Trigger
because Hebrew has a canonical five vowel inventory with no vowel reduction and a contrast
between fully voiced and voiceless unaspirated stops. The speaker read each word 3 times
from a printout, and was instructed to put stress on the first syllable of each item. Filler
words were added to the beginning and end of each column, so as to avoid prosodic effects
associated with list reading affecting experimental stimuli.
Table 1 contains all the anteriority experiment stimuli for the vowel pattern of [a,i] with all
combinations of consonants and suffixes. Table 2 shows the same for the voicing experiment.
Stem
pazi
tazi
kazi
pasi
tasi
kasi
patsi
tatsi
katsi
Stem
paZi
taZi
kaZi
paSi
taSi
kaSi
patSi
tatSi
katSi
Harmonic (-sa)
pazisa
tazisa
kazisa
pasisa
tasisa
kasisa
patsisa
tatsisa
katsisa
Harmonic (-Sa)
paZiSa
taZiSa
kaZiSa
paSiSa
taSiSa
kaSiSa
patSiSa
tatSiSa
katSiSa
Disharmonic (-Sa)
paziSa
taziSa
kaziSa
pasiSa
tasiSa
kasiSa
patsiSa
tatsiSa
katsiSa
Disharmonic (-sa)
paZisa
taZisa
kaZisa
paSisa
taSisa
kaSisa
patSisa
tatSisa
katSisa
Table 1: Examples of stimuli in the anteriority experiment
4.2
Design
Both experiments had one control group and one critical group. Participants were taught
how to make the plural form of a word in a made-up language by being shown a picture
of a single item with a bare stem and then two of that item with a suffixed form. In the
critical groups, the suffixed forms were always harmonic; in the control groups they were
half harmonic and half disharmonic.
The experiment consisted of a training phase and then a testing phase. The critical
groups were trained on stems and stem+suffix pairs exhibiting consonant harmony. For
example, in the anteriority experiment, if a critical participant were shown the stem [pazi],
then they would also be shown the suffixed form [pazisa], where the C2 and C3 share the
same value for the feature of anteriority, but not the suffixed form [paziSa], in which C2
and C3 do not share the same value for anteriority. In the voicing experiment, a critical
participant would be shown the stem [madi] with the suffixed form [madiba], where C2 and
C3 have the same value for voicing, but never [madipa]. The control groups were not shown
11
Voiceless Trigger
Voiced Trigger
Stem
mapi
napi
lapi
mati
nati
lati
maki
naki
laki
Stem
mabi
nabi
labi
madi
nadi
ladi
magi
nagi
lagi
Harmonic (-pa)
mapipa
napipa
lapipa
matipa
natipa
latipa
makipa
nakipa
lakipa
Harmonic (-ba)
mabiba
nabiba
labiba
madiba
nadiba
ladiba
magiba
nagiba
lagiba
Disharmonic (-ba)
mapiba
napiba
lapiba
matiba
natiba
latiba
makiba
nakiba
lakiba
Disharmonic (-pa)
mabipa
nabipa
labipa
madipa
nadipa
ladipa
magipa
nagipa
lagipa
Table 2: Examples of stimuli in the voicing experiment
any pattern in the items they were exposed to, that is, a stem like [pasi] had an equal chance
of being presented with either [pazisa] or [paziSa]. The critical groups in each experiment
were presented with all harmonic suffixed forms, while the control group saw 50/50 harmonic
and disharmonic pairs. The control training was also balanced for how many -sa endings and
how many -Sa endings a participant saw in the anteriority experiment, or how many -pa vs.
-ba endings a control participant saw in the voicing experiment. See Table 3 for an example
of the distribution of stimuli seen in each condition of the voicing experiment.
In the testing phase, each participant in all four conditions was asked to choose which
form of an item is correct in the language they were trained on. They were given a forced
choice between a harmonic form and a disharmonic form. All testing items were new to the
participants; none had been seen before in the training phase, but they contained the same
segments as the training items.
4.3
Procedure
The experiment was run using Experigen, an online platform created by Becker and Levine
(2010). Participants were told that they were going to learn words from an alien language,
and how to form the plural of those words. They were told that they need not memorize
words, but to pay attention to how the plural is formed, because later they would have to
do it themselves.
12
Critical Condition
Control Condition
Stem
mapi
napi
lapi
mati
nati
lati
maki
naki
laki
mabi
nabi
labi
madi
nadi
ladi
magi
nagi
lagi
mapi
napi
lapi
mati
nati
lati
maki
naki
laki
mabi
nabi
labi
madi
nadi
ladi
magi
nagi
lagi
Voicing
Plural (Suffixed)
mapipa
napipa
lapipa
matipa
natipa
latipa
makipa
nakipa
lakipa
mabiba
nabiba
labiba
madiba
nadiba
ladiba
magiba
nagiba
lagiba
mapiba
napipa
lapiba
matipa
natiba
latipa
makiba
nakipa
lakiba
mabiba
nabipa
labiba
madipa
nadiba
ladipa
magiba
nagipa
lagiba
Table 3: Examples of which stimuli are presented during training to participants in the critical and
control conditions of the voicing experiment. Bold represents harmonic forms.
4.3.1
Training Phase
During the training phase, participants were shown pictures with associated lexical items.
The stimuli were presented in audio form as well as orthographically. I used standard English
13
spellings for the phonemes that have an unambiguous letter associated with them, and to
represent [Z], the only phoneme without a canonical English spelling, I used “zh.”
First, a picture of a single item appeared with the phrase “This is a
” above it. A
stem form of a stimulus item was in the blank, (e.g. “tucho”) (See Figure 3). An audio play
button accompanied each stimulus item, and it was necessary to press the button and listen
to the audio file before proceeding.
Figure 3: Training Trial
Next, the participants were shown a picture of two of that same item with the phrase
“These are
” above it. A suffixed form of the stimulus item was in the blank (e.g.“tuchosha”).
The goal was to teach the participant how to form the plural of a word in this language by
adding one of the two possible suffixes (See Figure 4). The pictures were paired randomly
with the stimulus items, and the same words and picture were not associated with each other
for all participants.
14
Figure 4: Training Trial
Each participant was shown 26 such pairs of pictures, 20 including environments where
harmony could occur, and 6 fillers. The set of stimuli that each participant in each group
saw was randomly selected from the total set of stimuli, so each participant saw them in a
different order, and a different breakdown between which stimuli were seen in training and
which in testing.
4.3.2
Testing Phase
Once the training phase was over, the participant was told that now it was their turn to
provide the plural forms. 42 trials followed, 36 with potential harmony environments, and
6 fillers. During each trial, participants were first shown a picture of a single object and
its associated lexical item, as in the training phase. But then the participant was shown
the picture of two of that item and asked to provide the plural form of the lexical item.
15
They were given a two-alternative forced choice test. During each trial, the participant was
presented a harmonic form and a disharmonic form (e.g. “Are these pasisa or pasisha?”)
and asked to choose which was correct in the language they had just learned. Again, the
participant had to listen to the audio file of each stimulus before buttons appeared at the
bottom to make their choice (See Figure 5).
Figure 5: Testing Trial
16
4.4
Participants
The participants were 400 adult native English speakers (100 participants per each of the
4 experimental conditions), recruited through Amazon Mechanical Turk (AMT), Amazon’s
crowdsourcing website (www.mturk.com) and paid $0.75 to complete the experiment, which
took about 10 minutes. AMT has been shown to produce results to a linguistic study that are
indistinguishable from an identical study conducted in a laboratory setting (Sprouse 2010).
The participants were told that they must be native speakers of English to do the task,
and were asked at the end in a brief demographic survey to report their native language.
Additionally, participants were restricted to those which AMT detected as having an IP
address in the United States. Responses were discarded if the participant self-reported as a
native speaker of any language other than English. English does not exhibit a categorical
pattern of consonant harmony across a vowel, and any other bias that English speakers may
have from other subcategorical properties of the language are controlled for by the control
conditions. 5 participants were excluded before data analysis because they had answered
with the same ending for 100% of their testing trials. This leaves the total N=395 for the
results presented below.
5
Results
The responses from each participant’s testing phase were coded for whether they were harmonic or not, i.e. whether the ending chosen for the stem agreed with the trigger (C2 ) for
the feature at hand, either voicing or anteriority. For each participant, there were 36 binary
data points.
A Mixed Logit Model was fit1 using the lmer() function in the lme4 package (Bates &
Maechler 2010) for the R software (http://www.R-project.org.) The dependent variable was
whether the response was harmonic or not. The predictors in the model were feature (anteriority or voicing) and condition (critical or control), and the interaction between condition
and feature. Random intercepts were included for participant and stimulus stem. Random
slopes were not included for subjects, because subjects only participated in one treatment
group each. Random slopes by stimulus item were also not included since the same items
were not used in all four conditions (though the same items were used for the control and
critical training conditions for a single feature). There is a significant main effect of condition
and a significant interaction between condition and feature. The full model is given in Table
4.
intercept
condition
feature
condition:feature
Estimate
−0.253
2.135
0.170
−1.332
Standard Error
0.1257
0.184
0.263
0.322
Wald’s z
−2.013
11.626
0.648
−4.136
p
0.044
< .0001
0.517
< .0001
Table 4: Results of a Mixed Logit Model with dependent variable of harmonic responses, testing for
main effects of condition (baseline=control) and feature (baseline=anteriority) and an interaction
between condition and feature.
1
lmer(correct∼condition+feature+condition:feature+(1—userCode)+(1+condition—root), family=“binomial”)
17
The results are shown graphically in Figure 6. The main effect of condition is significant,
because in both experiments, the participants in the critical group gave a higher proportion
of harmonic answers than did those in the control groups (p < .0001, 76.4% vs. 44.6% in the
anteriority experiment, and 63.0% vs. 48.0% in the voicing experiment). The main effect
of feature was not significant, showing that the proportion of overall harmonic responses
was not affected by the harmonic feature. The significant interaction between condition and
feature (p < .0001) results from the larger difference between the performance of the control
and critical groups in the anteriority experiment compared to the voicing experiment. The
anteriority experiment has a difference between the two conditions of 31.8% while the voicing
experiment has a difference of 15%. Participants learned the anteriority pattern better than
the voicing pattern, and the improvement in harmonic responses from the control group to
the critical group was twice as big in the anteriority experiment as in the voicing experiment.
Figure 6: Proportion of harmonic responses given in each experiment, by condition. Error bars
indicate the standard error of the mean.
The data from the critical groups of both experiments were also analyzed by feature value
of the trigger consonant, comparing the proportion of correct harmonic responses that were
[−feature] and [+feature]. For example, in the anteriority experiment, answering [pazisa] to
the given stem [pazi] is an instance of correctly providing harmony of the [+anterior] feature,
while giving the plural [patSiSa] to the given stem [patSi] is also a harmonic response, but
it matches on the value of [−anterior]. Analogously, [padiba] is harmonic on the value of
[+voice], while [patipa] is harmonic on the value of [−voice].
To test for any differences between feature values, another Mixed Logit Model was fit
18
to just the data from the critical conditions, not the control data. The dependent variable
was whether the response was harmonic or not. The predictors in the model were feature
(anteriority or voicing) and feature value of the trigger consonant ([+feature] or [−feature]),
and the interaction between feature and feature value. Random intercepts were included for
participant. There is a significant main effect of feature, but no significant effect of feature
value. The interaction between feature and feature value was significant. The full model is
given in Table 5.
intercept
feature value
feature
feature value:feature
Estimate
2.254
0.030
−1.10
−0.710
Standard Error
0.212
0.098
0.290
0.124
Wald’s z
10.625
0.308
−3.779
−5.712
p
< .0001***
0.758
.0002 ∗ ∗
< .0001***
Table 5: Results of a Mixed Logit Model with dependent variable of harmonic responses, testing
for main effects of feature value (baseline=[−feature]) and feature (baseline=anteriority) and an
interaction between feature value and feature.
The results are shown graphically in Figure 7. As expected, in this analysis the main effect
of feature is significant, because overall participants in the critical anteriority experiment gave
more harmonic responses than those in the critical voicing group, across both [+feature] and
[−feature] cases. This is consistent with the main analysis presented above. The main effect
of feature value was not significant, and there is no reason to believe that [+voice] and
[+anteriority] would pattern together or that [−voice] and [−anteriority] would do so either.
Both anteriority and voicing are included in the same model here strictly to compare the
trend between plus and minus feature between the two experiments. The interaction between
feature and feature value was significant, because there was no difference between [+anterior]
and [−anterior] but there was a significant difference between [+voice] and [−voice]. Of all
the trials where the trigger consonant was [−voice], 69.2% were answered correctly, but only
56.8% of the [+voice] trials were answered correctly.
19
Figure 7: Proportion of harmonic responses given based on whether the trigger consonant is [+feature] or [−feature].
Data from the critical training conditions were further examined for an effect of specific
trigger consonant. The data from the critical training condition of the anteriority experiment
was analyzed separately from that of the critical training condition of the voicing experiment.
This analysis was done to see if any aggregate results were due to particular triggers behaving
differently from the others, particularly to see if the learnability could have been attributed
to identity effects. It might have been easier for participants to choose the harmonic response
when the trigger consonant was identical to the target consonant (e.g. [pasisa]) as opposed
to when the target was harmonic with the trigger but not identical (e.g. [pazisa]). Many
languages distinguish between identical and non-identical segments in phonotactic patterns,
and identity has previously been assumed to be a property that phonological constraints
can reference (MacEachern 1999; Coetzee & Pater 2008). If there were identity effects, then
the triggers [s] and [S] in the anteriority experiment, and triggers [b] and [p] in the voicing
experiment would show significantly higher rates of correct answers than the other triggers
in their respective experiments, as participants would be matching identical segments better
than ones that only agree in the feature.
This analysis also illustrated whether the trigger [ts] behaved differently than other consonants, which might be expected because it only appears in English at the end of words
and across morpheme boundaries and thus is not a phoneme of English, and also whether
[Z] behaved differently because it is an uncommon phoneme in English.
Table 6 shows the results of a Mixed Logit Model with the dependent variable being
20
harmonic responses and the independent variable being trigger consonants from the anteriority experiment [s, z, ts, S, Z, tS]. The six level factor was dummy coded, with [tS] as the
baseline, and the other five consonants are compared to it. Random intercepts were included
for participants.
intercept ([tS])
[s]
[S]
[ts]
[z]
[Z]
Estimate
2.437
0.528
0.315
0.163
0.263
0.540
Standard Error
0.327
0.175
0.171
0.173
0.173
0.175
Wald’s z
7.452
3.024
1.841
0.945
1.522
3.080
p
< .0001***
0.003*
0.066
0.345
0.128
0.002*
Table 6: Results of a Mixed Logit Model with dependent variable of harmonic responses, testing
for main effect of trigger consonant.
There was a significant difference (p< .01) between [tS], which had the lowest rate of
harmonic responses, and the two consonants that had the highest rates of harmonic responses
[s] and [Z]. The model found no other significant results. The results for the anteriority trigger
consonants are presented graphically in Figure 8.
Figure 8: Harmonic responses by trigger consonant for the anteriority experiment
The results show that matching on identity of the segment does not across the board
make it easier to choose a harmonic response, as here [s] as a trigger consonant got slightly
21
higher rates of harmonic responses (80%) than did the other two anterior consonants, but the
differences were not significant per a Tukey’s posthoc test. [S] actually did worse (76%) than
[Z] (80%) and not significantly different from [tS] (73%). The graph in Figure 8 also shows
that the trigger [ts] does not behave significantly differently than the other five triggers
in the experiment, which could be expected due to evidence that [ts] is not treated as a
single affricate phoneme by native English speakers. Similarly, there is no aberrant behavior
observed for the consonant [Z] either (there is only a significant difference between [Z] and
[tS], but [Z] actually performs better, p=.025), even though it is an uncommon sound in
English. This serves as a check that it was valid to use [ts] and [Z] in the experiment as part
of the sibilant series. The two affricates [ts] and [tS] have the lowest percentages of harmonic
responses given.
Table 7 shows the results of a Mixed Logit Model with the dependent variable being
harmonic responses and the independent variable being trigger consonants from the voicing
experiment [b, d, g, p, t, k]. The six level factor was dummy coded, with [b] chosen by the
model as the baseline, and the other five consonants compared to it. Random intercepts
were included for participants.
intercept ([b])
[d]
[g]
[k]
[p]
[t]
Estimate
0.725
−0.525
−0.466
0.262
0.389
0.317
Standard Error
0.144
0.128
0.129
0.133
0.133
0.133
Wald’s z
5.029
−4.095
−3.623
1.980
2.925
2.389
p
< .0001***
< .0001***
< .001**
0.048
0.003*
0.017
Table 7: Results of a Mixed Logit Model with dependent variable of harmonic responses, testing
for main effect of trigger consonant.
The model found that [b] had significantly more harmonic responses than [d] with a
p < .0001 and significantly more than [g] with a p < .001. The trigger consonant [b] was also
found to have significantly fewer harmonic responses than the trigger consonant [p] with a
p < .01. The results for the voicing trigger consonants are presented graphically in Figure 9.
22
Figure 9: Harmonic responses by trigger consonant for the voicing experiment
[b] got significantly more harmonic responses (63%) as a trigger than did [d] (54%) or
[g] (55%), which is consistent with an identity advantage, but the same is not true for the
voiceless consonants. [p] did not get more correct responses than [t] or [k] (all three were
around the same, between 68-70% correct), which is not consistent with an identity effect.
All three voiced consonants did worse than the voiceless consonants, so the effect in Figure
7 above, where the [−voice] triggers have significantly higher rates of harmonic responses
than the [+voice] triggers, is not due to disproportionate effects of only one trigger in the
category.
6
Discussion
The results of the experiments show that participants in the critical training groups learned
both anteriority harmony as well as voicing harmony, but that the anteriority pattern was
learned better. As seen in Figure 7, there was no significant difference between [+anterior]
and [−anterior] triggers, but [−voice] triggers got significantly more harmonic responses than
did [+voice] triggers. The difference in results here between [+voice] and [−voice] triggers
is actually contra the phonetic grounding, as harmony of [+voice] is phonetically grounded
because the intervening vowel is also voiced, but harmony of [−voice] is not grounded. The
typological facts reflect this, with patterns like the one in Ngizim being asymmetrical, only
applying to harmony of the [+voice] vowel.
The results broken down by specific trigger consonant show that [Z], which is an un23
common segment in English, and [ts], which is not a phoneme in English, do not behave
significantly differently than the other consonants. It also does not seem to be easier to
choose a harmonic response when the target consonant is identical to the trigger consonant
than when they are non-identical but share a feature. Place of articulation did not have a
consistent affect on harmonic responses in the voicing experiment.
English does have at least two phonological patterns that involve voicing assimilation,
the plural -s morpheme which takes forms /s/ and /z/, and the past tense -ed morpheme,
which takes forms /t/ and /d/. In both cases, the underlying consonant assimilates to
the preceding consonant in voicing, i.e./ kæts/ vs /dOgz/ and /klæpt/ vs /taImd/. This
pattern does not qualify as harmony in the sense that Hansson (2001) and Gafos (1999)
are dealing with, because it does not have, at minimum, an intervening vowel between the
two harmonizing consonants. However, it’s still possible to imagine that this familiarity
with voicing agreement could affect English speaker’s performance in the experiments, since
there is no comparable pattern in English involving anteriority. However, my results do not
show any effect of bias towards voicing harmony in the control condition, and the poorer
performance on the voicing condition goes in the opposite direction as predicted if native
phonology is a main factor.
Another way that the features of anteriority and voicing are different is that anteriority
is clearly a binary feature with [+anterior] and [−anterior] values, but it has been argued
that VOICE is privative, and that [−voice] does not actually exist. This view could be
corroborated by the typological evidence that in the few patterns that have been described
as voicing harmony, it is common for the system to be asymmetric such that only voiceless
consonants become voiced and not the other way around, such as in Ngizim and Kera
described above. This would make sense if [−voice] didn’t exist and it was just the presence
or absence of a privative VOICE participating in the assimilation. What this difference in
feature binarity would mean for the comparison of the learnability of anteriority or voicing
harmony is unclear, and the effects could be confounded with the lack of phonetic grounding
of [−voice] harmony because of the articulatory gestures involved. As discussed above, in
my voicing harmony experiment, the participants actually did better on choosing harmonic
forms when the trigger was [−voice] than when it was [+voice], which is not inline with
the typological data, the phonetic grounding, or what predicted effects of feature privativity
might be.
7
Conclusion
The results of the experiments in this paper show a clear difference in how well participants
learned anteriority harmony and voicing harmony. Both patterns were learned, but anteriority harmony was learned significantly better. This is in line with the phonetic grounding
of the two patterns. Anteriority is a feature produced by the tongue tip and tongue body,
and this gesture can be held through a vowel without affecting the percept of the vowel.
The glottal opening and closing gestures that produce voicing do affect the production of
the vowel, and an open glottis (required for voiceless consonants) cannot be held through a
vowel without making it voiceless too. Because of this, anteriority is phonetically grounded
with respect to consonant harmony across an intervening vowel, while voicing harmony is not.
In addition, the typological facts show that anteriority harmony is robustly attested cross
linguistically, and there are many cases of fully symmetric and nearly exceptionless patterns.
24
Voicing harmony, on the other hand, is scantily attested and the few existing examples are
marginal. While my results do not suggest any causal link in any direction between these
three facts, it remains that the learnability of anteriority harmony over voicing harmony
found in my experiments is in line with both the phonetic grounding and typological facts.
The results in Figure 6 show that it is not the case that voicing harmony wasn’t learned at
all. Both patterns were learned at significantly higher rates in the critical condition than in
the control condition, but anteriority harmony was learned much better. In her paper about
naturalness bias, Carpenter posits two separate cognitive-mechanisms for pattern leaning,
one that is general and one that is language-specific. In this view, the general mechanism is
used for all pattern learning, but when natural linguistic substance is involved, the languagespecific learning mechanism is also engaged, doing the additional work that exhibits itself in
higher rates of successful learning of the pattern. My results would fit with such a model,
where the general pattern learning mechanism allowed voicing harmony to be learned to an
extent, but a specific language learning mechanism privileged anteriority harmony (whether
because of its phonetic grounding or some other reason) as a linguistic pattern rather than a
non-linguistic abstract pattern, and allowed the pattern to be learned more quickly or better
by the participants.
This paper shows that adult native English speakers show a bias towards anteriority
harmony, but there are several explanations for why this might be. An analysis of the English
lexicon could be performed to find out if there are any statistical biases in the language that
could influence speakers to be more familiar with, or do better at learning, the anteriority
harmony patterns. Since the quality of the headphones that participants (recruited through
Amazon Mechanical Turk) used could not be controlled, the experiment could be duplicated
in a laboratory environment to see if the same learning asymmetry would occur with better
quality equipment. The experiment could also be repeated with the stimuli recorded by an
English speaker, to see if participants were influenced by the non-native voicing distinctions
produced by the Hebrew speaker used in this study. In these experiments, participants were
asked to listen to stimuli and perform a forced-choice task. For further research in this area,
a production study could be undertaken to measure the learnability of the patterns when
participants are asked to produce the harmonic forms. Additionally, the study could be
duplicated using a phonotactic training method to see if the patterns are still learned to the
same degree. Different amounts of training can be provided to find at what point the learner
has enough exposure to learn the patterns.
25
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