We are getting closer to the end of my list of open problems in computational
diversity linguistics. After this post, there is only one left, for November, followed by an outlook and a wrap-up in December.
In
last month's post, devoted to the
Typology of semantic change, I
discussed the general aspects of a
typology in linguistics, or — to be more
precise — how I think that linguists use the term. One of the necessary conditions for a typology to be meaningful is that the
phenomenon under questions shows enough similarities across the languages of
the world, so that patterns or tendencies can be identified regardless of the
historical relations between human languages.
Sound change in this context refers to a very peculiar phenomenon
observed in the change of spoken languages, by which certain sounds in the
inventory
of a given language change their pronunciation over time. This often occurs across
all
of the words in which these sounds recur, or across only those sounds which appear
to occur
in specific phonetic contexts.
As I have discussed this phenomenon in
quite a few past blog posts, I will not discuss it any more here, but I will
rather simply refer to the specific task, that this problem entails:
Assuming (if needed) a given time frame, in which the change occurs,
establish a general typology that informs about the universal tendencies
by which sounds occurring in specific phonetic environments are subject
to change.
Note that my view of "phonetic environment" in this context includes
an environment that would capture all possible contexts. When
confronted with a sound change that seems to affect a sound in all
phonetic contexts, in which the sound occurs in the same way, linguists
often speak of "unconditioned sound change", as they do not find any
apparent condition for this change to happen. For a formal treatment,
however, this is unsatisfying, since the lack of a phonetic environment
is also a specific condition of sound change.
Why it is hard to establish a typology of sound change
As is also true for semantic change, discussed as
Problem 8 last month, there are
three major reasons why it is hard to establish a typology of sound change. As a first problem, we
find, again, the issue of acquiring the data needed to establish the typology. As a second problem, it is also not clear how to handle the
data appropriately in order to allow us to study sound change across different
language families and different times. As a third problem, it is also very
difficult to interpret sound change data when trying to identify
cross-linguistic tendencies.
Problem 1
The problem of acquiring data about sound change processes in sufficient size is
very similar to the problem of semantic change: most of what we know about
sound change has been inferred by comparing languages, and we do not know how
confident we can be with respect to those inferences. While semantic change is
considered to be notoriously difficult to handle (
Fox 1995:
111), scholars generally have more confidence in sound change and
the power of linguistic reconstruction. The question remains, however, as to how
confident we can really be, which divides the field into the so-called "realists" and
the so-called "abstractionalists" (see
Lass 2017 for a recent discussion of the debate).
As a typical representative of abstractionalism in linguistic reconstruction,
consider the famous linguist Ferdinand de Saussure, who emphasized that the
real sound values which scholars reconstructed for proposed ancient words in
unattested languages like, for example, Indo-European, could as well be simply
replaced by numbers or other characters, serving as identifiers (
Saussure
1916: 303). The fundamental idea here, when reconstructing
a word for a given proto-language, is that a reconstruction does not need to
inform us about the likely pronunciation of a word, but rather about the
structure of the word in contrast to other words.
This aspect of historical linguistics is often difficult to discuss with
colleagues from other disciplines, since it seems to be very peculiar, but it
is very important in order to understand the basic methodology. The general
idea of structure versus substance is that, once we accept that the words in
a languages are built by drawing letters from an alphabet, the letters
themselves do not have a substantial value, but have only
a value in contrast to other letters. This means that a sequence, such as
"ABBA" can be seen as being structurally identical with "CDDC", or "OTTO". The
similarity should be obvious: we have the same letter in the beginning and the
end of each word, and the same letter being repeated in the middle of
each word (see
List 2014: 58f for a closer discussion of this
type of similarity).
Since sequence similarity is usually not discussed in pure structural terms,
the abstract view of correspondences, as it is maintained by many historical
linguists, is often difficult to discuss across disciplines. The reason why
linguists tend to maintain it is that languages tend to change not only their
words by mutating individual sounds, but that whole sound systems change, and
new sounds can be gained during language evolution, or lost (see
my blogpost from March 2018 for a closer elaboration of the problem of sound change).
It is important to emphasize, however, that despite prominent abstractionalists
such as Ferdinand de Saussure (1857-1913), and in part also Antoine Meillet
(1866-1936), the majority of linguists think more realistically about their
reconstructions. The reason is that the composition of words based on sounds
in the spoken languages of the world usually follows specific rules, so-called
phonotactic rules. These may vary to quite some degree among languages, but
are also restricted by some natural laws of pronunciability. Thus,
although languages may show impressively long chains of one consonant
following another, there is a certain limit to the number of consonants that
can follow each other without a vowel. Sound change is thus believed
to originate roughly in either production (speakers want to pronounce things in a
simpler, more convenient way) or perception (listeners misunderstand words and
store erroneous variants, see
Ohala 1989
for details). Therefore, a reconstruction of a given sound system based on the
comparison of multiple languages gains power from a realistic
interpretation of sound values.
The problem with the abstractionalist-realist debate, however, is that linguists
usually conduct some kind of a mixture between the two extremes. That means that
they may reconstruct very concrete sound values for certain words, where they
have very good evidence, but at the same time, they may come up with abstract
values that serve as place holders in lack of better evidence. The most famous
example are the Indo-European "laryngeals", whose existence is beyond
doubt for most historical linguistics, but whose sound values cannot be
reconstructed with high reliability. As a result, linguists tend to spell them
with subscript numbers as
*
h₁,
*
h₂, and
*
h₃. Any attempt to
assemble data about sound change processes in the languages of the world needs to
find a way to cope with the different degrees of evidence we find in linguistic
analyses.
Problem 2
This leads us directly to our second problem in handling sound change data
appropriately in order to study sound change processes. Given that many
linguists propose changes in the typical
A > B / C
(A
becomes B in
context C) notation, a possible way of thinking about establishing a first
database of sound changes would consist of typing these changes from the
literature and making a catalog out of it. Apart from the interpretation of the
data in abstractionalist-realist terms, however, such a way of collecting the
data would have a couple of serious shortcomings.
First, it would mean that the
analysis of the linguist who proposed the sound change is taken as final,
although we often find many debates about the specific triggers of sound
change, and it is not clear whether there would be alternative
sound change rules
that could apply just as well (see
Problem
3
on the task of automatic sound law induction for details). Second, as
linguists tend to report only what changes, while disregarding what does
not
change, we would face the same problem as in the
traditional study of semantic change: the database would suffer from a
sampling bias, as we could not learn anything about the stability of
sounds. Third, since sound change depends not only on production and
perception, but also on the
system of the language in which
sounds are produced, listing sounds deprived of examples in real words
would most likely make it impossible to take these
systemic aspects of sound change into account.
Problem 3
This last point now leads us to the third general difficulty, the question of
how to interpret sound change data, assuming that one has had the chance
to acquire enough of it from a reasonably large sample of spoken languages. If
we look at the general patterns of sound change observed for the
languages of the world, we can distinguish two basic conditions of sound
change,
phonetic conditions and
systemic conditions. Phonetic conditions
can be further subdivided into
articulatory (= production) and
acoustic
(= perception) conditions. When trying to explain why certain sound changes can
be observed more frequently across different languages of the world, many
linguists tend to invoke phonetic factors. If the sound
p,
for example, turns into an
f, this is not necessarily surprising given the
strong similarity of the sounds.
But similarity can be measured in two ways:
one can compare the similarity with respect to the production of a sound by a
speaker, and with respect to the perception of the sound by a listener. While
production of sounds is traditionally seen as the more important factor
contributing to sound change (
Hock 1991: 11), there are clear
examples for sound change due to misperception and re-interpretation by the
listeners (Ohala 1989: 182). Some authors go as far as to claim that
production-driven changes reflect regular internal language change (which
happens gradually during acquisition, or (depending on the theory) also in
later stages (
Bybee 2002), while perception-based changes
rather reflect change happening in second language acquisition and language
contact (
Mowrey and Pagliuca 1995: 48).
While the interaction of production and perception has been discussed in some
detail in the linguistic literature, the influence of
systemic factors has so
far been only rarely regarded. What I mean by this factor is the idea that
certain changes in language evolution may be explained exclusively as resulting
from systemic constellations. As a straightforward example, consider the
difference in
design space for the production of
consonants,
vowels, and
tones. In order to maintain pronunciability and comprehensiblity, it is
useful for the sound system of a given language to fill in those spots in the
design space that are maximally different from each other. The larger the
design space and the smaller the inventory, the easier it is to guarantee its
functionality. Since design spaces for vowels and tones are much smaller than
for consonants, however, these sub-systems are more easily disturbed, which
could be used to explain the presence of chain shifts of vowels, or flip- flop
in tone systems (
Wang 1967: 102). Systemic considerations play
an increasingly important role in evolutionary theory, and, as shown in List et
al. (
2016), also be used as explanations for phenomena as
strange as the phenomenon of Sapir's drift (
Sapir 1921).
However, the crucial question, when trying to establish a typology of sound change,
is how these different effects could be measured. I think it is
obvious that collections of individual sound changes proposed in the literature
are not enough. But what data
would be sufficient or needed to address the
problem is not entirely clear to me either.
Traditional approaches
As the first traditional approach to the typology of sound change, one should
mention the intuition inside the heads of the numerous historical linguists who
study particular language families. Scholars trained in historical linguistics
usually start to develop some kind of intuition about likely and unlikely
tendencies in sound change, and in most parts they also agree on this. The
problem with this intuition, however, is that it is not explicit, and it seems
even that it was never the intention of the majority of historical linguists
to make their knowledge explicit. The reasons for this reluctance with respect
to formalization and transparency are two-fold. First, given that every
individual has invested quite some time in order to grow their intuition, it is
possible that the idea of having a resource that distributes this intuition in
a rigorously data-driven and explicit manner yields the typical feeling of
envy in quite a few people who may then think: «I had to invest so much time in
order to learn all this by heart. Why should young scholars now get all this
knowledge for free?» Second, given the problems outlined in the previous
section, many scholars also strongly believe that it is impossible to formalize
the problem of sound change tendencies.
The by far largest traditional study of the typology of sound change is
Kümmel's (
2008) book
Konsonantenwandel (
Consonant Change), in which the author surveys sound change processes discussed in the
literature on Indo-European and Semitic languages. As the title of the book
suggests, it concentrates on the change of consonants, which are (probably
due to the larger design space) also the class of sounds that shows stronger
cross-linguistic tendencies. The book is based on a thorough inspection of
the literature on consonant change in Indo-European and Semitic linguistics.
The procedure by which this collection was carried out can be seen as the
gold standard, which any future attempt of enlarging the given collection
should be carried out.
What is specifically important, and also very difficult to achieve, is the
harmonization of the evidence, which is nicely reflected in Kümmel's
introduction, where he mentions that one of the main problems was to determine
what the scholars actually meant with respect to phonetics and phonology, when
describing certain sound changes (Kümmel 2008: 35). The major drawback of the
collection is that it is not (yet) available in digital form. Given the
systematicity with which the data was collected, it should be generally
possible to turn the collection into a database; and it is beyond doubt that
this collection could offer interesting insights into certain tendencies of
sound change.
Another collection of sound changes collected from the literature is the
mysterious
Index Diachronica, a collection of sound changes collected from
various language families by a person who wishes to remain anonymous. Up to now, this collection even has a
Searchable
Index that allows scholars to click
on a given sound and to see in which languages this sound is involved in some
kind of sound change. What is a pity about the resource is that it is difficult
to use, given that one does not really know where it actually comes from, and
how the information was extracted from the sources. If the
anonymous author would only decide to put it (albeit anonymously, or under
a pseudonym) on a public preprint server, such as, for example,
Humanities
Commons, this would be excellent, as it would
allow those who are interested in pursuing the idea of collecting sound changes
from the literature an excellent starting point to check the sources, and to
further digitize the resource.
Right now, this resource seems to be mostly used by
conlangers, ie., people
who create artificial languages as a hobby (or profession). Conlangers are
often refreshingly pragmatic, and may come up with very interesting and creative
ideas about how to address certain data problems in linguistics, which "normal"
linguists would refuse to do. There is a certain tendency in our field to
ignore certain questions, either because scholars think it would be too tedious
to collect the data to address that problem, or they consider it
impossible to be done "correctly" from the start.
As a last and fascinating example, I have to mention the study by
Yang and Xu
(2019), in which the authors review studies of concrete examples
of tone change in South-East Asian languages, trying to identify
cross-linguistic tendencies. Before I read this study, I was not aware that
tone change had at all been studied concretely, since most linguists consider
the evidence for any kind of tendency far too shaky, and reconstruct tone
exclusively as an abstract entity. The survey by Yang and Xu, however, shows
clearly that there seem to be at least some tendencies, and that they can be
identified by invoking a careful degree of abstraction when comparing tone
change across different languages.
For the detailed reasons outlined in the previous paragraph,
I do not think that a collection of sound change examples from the
literature addresses the problem of establishing a typology of sound
change. Specifically, the fact that sound change collections usually do
not provide any tangible examples or frequencies of a given sound change
within the language where it occurred, but also the fact that they do
not offer any tendencies of sounds to
resist change, is a major
drawback, and a major loss of evidence during data collection.
However, I consider these
efforts as valuable and important contributions to our field. Given that
they allow us to learn a lot about some very general and well-confirmed
tendencies of sound change, they are also an invaluable source of
inspiration when it comes to working on alternative approaches.
Computational approaches
To my knowledge, there are no real computational approaches to the study of
sound change so far. What one should mention, however, are initial attempts to
measure certain aspects of sound change automatically. Thus,
Brown et al.
(2013) measure sound
correspondences across the world's
languages, based on a collection of 40-item wordlists for a very large sample
of languages. The limitations of this study can be found in the restricted
alphabet being used (all languages are represented by a reduced transcription
system of some 40 letters, called the
ASJP
code. While the code originally
allowed representing more that just 40 sounds, since the graphemes can be
combined, the collection was carried out inconsistently for different
languages, which has now led to the situation that the majority of
computational approaches treat each letter as a single sound, or consider
only the first element of complex grapheme combinations.
While sound change is a directional process, sound correspondences reflect the
correspondence of sounds in different languages as a result of sound change,
and it is not trivial to extract directional information from sound
correspondence data alone. Thus, while the study of Brown et al. is a very
interesting contribution, also providing a very straightforward methodology, it
does not address the actual problem of sound change.
The study also has other limitations. First, the approach only measures those cases
where sounds
differ in two languages, and thus we have the same problem that we
cannot tell how likely it is that two
identical sounds
correspond. Second, the study ignores
phonetic environment (or
context),
which is an important factor in sound change tendencies (some sound changes,
for example, tend to occur only in word endings, etc.). Third, the study
considers only sound correspondences across language
pairs, while it is clear
that one can often find stronger evidence for sound correspondences when
looking at multiple languages (
List 2019).
Initial ideas for improvement
What we need in order to address the problem of establishing a true typology of
sound change processes, are, in my opinion:
- a standardized transcription
system for the representation of sounds across linguistic resources,
- increased amounts of readily coded data that adhere to the standard
transcription system and list cognate sets of ancestral and descendant
languages,
- good, dated phylogenies that allow to measure how often sound
changes appear in a certain time frame,
- methods to infer the sound change
rules (Problem
3), and
- improved methods for ancestral state reconstruction that would allow us to
identify sound change processes not only for the root and the descendant nodes,
but also for intermediate stages.
It is possible that even these five points are not enough yet, as I am still
trying to think about how one should best address the problem. But what I can say for
sure is that one needs to address the problem step by step, starting with the
issue of standardization — and that the only way to account for the problems
mentioned above is to collect the pure empirical evidence on sound change, not
the summarized results discussed in the literature. Thus, instead of saying
that some source quotes that in German, the
t became a
ts at some point, I
want to see a dataset that provides this in the form of concrete examples that are
large enough to show the regularity of the findings and ideally also list the
exceptions.
The advantage of this procedure is that the collection is independent of
the typical errors that usually occur when data are collected from the literature
(usually also by employing armies of students who do the "dirty" work for the
scientists). It would also be independent of individual scholars'
interpretations. Furthermore, it would be exhaustive — that is, one could measure
not only the frequency of a given change, but also the regularity, the
conditioning context, or the systemic properties
The disadvantage is, of course, the need to acquire standardized data in a
large-enough size for a critical number of languages and language families.
But, then again, if there were no challenges involved in this endeavor, I would not present
it as an open problem of computational diversity linguistics.
Outlook
With the newly published database of Cross-Linguist Transcription Systems
(
CLTS,
Anderson et al. 2018), the
first step towards a rigorous standardization of transcription systems has
already been made. With our efforts towards a standardization of wordlists
that can also be applied in the form of a retro-standardization to existing data
(
Forkel et al. 2018), we have proposed a further step of
how lexical data can be collected efficiently for a large sample of the worlds'
spoken languages (see also
List et al. 2018). Work on
automated cognate detection and workflows for computer-assisted language
comparison has also drastically increased the efficiency of historical language
comparison.
So, we are advancing towards a larger collection of high-quality and
historically compared datasets; and it is quite possible that we
will, in a couple of years from now, arrive at a point where the
typology of sound change is no longer a dream by me and many colleagues,
but something that may actually be feasible to extract from
cross-linguistic data that has been historically annotated.
But until then, many issues still remain unsolved; and in order to
address these, it would be useful to work towards pilot studies, in
order to see how well the ideas for improvement, outlined above, can
actually be implemented.
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