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The effect of climate on individual speech: Does Larry King use more vowels when it’s warmer?

This weekend I appeared in an NPR article about Ian Maddieson and Christophe Coupe’s work on the effects of climate and ecology on the sound systems of languages.  I haven’t read the study itself, but I did get to see the slides that Maddieson and Coupe presented this week at the Acoustical Society of America.  Essentially, they find that speech sounds have high efficacy – adaptation to being transmitted and received in the local ecology.  Specifically, languages tend to be more sonorous (less ‘consonant heavy’) in warmer places with more tree cover.  This makes sense, since these kind of sounds are better at cutting through these obstacles.

I was interviewed for about an hour, but the quotes from me in the piece are actually a bit out of context.  For instance, I claim that this is the first study of its kind, when there have been several studies which looks at climate and language (including one I co-authored with Caleb Everett and Damian Blasi).  But, to be fair, Maddieson and Coupe’s study is probably the one with the greatest range of ecological variables and most sophisticated linguistic measure (although I’m not sure yet how they control for historical relatedness).

You can read about the study in the article above, but I wanted to address another thing I’m quoted as saying.  The interviewer asked if it was possible to see these effects in a single language or a single speaker, and I said that it was very unlikely, but that I’d tried to do this with transcripts of Larry King.  I went on to say that I absolutely wouldn’t publish this because it was a crazy idea that nobody would believe.

But now the cat’s out of the bag,  so here’s what I found.

Does Larry King use more vowels when it’s warmer?

If we see language change as natural selection operating on individual utterances in conversation (a la Croft and others), then we should be able to see selective pressures at work in the utterances of an individual speaker.  This should also apply to the influence of climate.  Given enough data, you should be able to see an individual adapting over the seasons.  In light of Maddieson and Coupe’s hypothesis, speakers should use proportionately more vowels compared to consonants when it’s warmer.

CNN provides transcripts for every show broadcast between 2000 and 2012.  Larry King has done an interview practically every day on the show ‘Larry King Live’ (which has been used before in linguistic studies), so I extracted Larry King’s speech transcripts (excluding the guest’s speech, mentions of the location of the studio and the guest’s names).  For each transcript I counted the frequency of each letter, then calculated the ratio of vowels (aeiouy) to consonants.    Then, for each air date, I found the actual temperature and humidity data for that date and the location of the show (CNN studios in LA). The show is occasionally recorded in Washington DC or New York.  I tried to detect these automatically and matched them with the climate measures for the CNN studios in those cities.

There are about 3,500 transcripts over 11 years, about 90% of which were aired on consecutive days. (I know nothing about this show, and am a bit surprised by its frequency!  I’ll have to check whether the transcripts include repeats).

Here is a depiction of the results for temperature and humidity:


The Black lines show King’s vowel ratio (higher = more vowels) and bars are 95% confidence intervals around the mean for each week of the year.  The maximum and minimum temperature are shown in red and blue.  Below is a similar graph for specific humidity.


Surprisingly, there is some variation in proportion of vowels, and it looks like there’s a trend in the right direction.

To analyse the data, I used a linear mixed effects model, predicting vowel ratio by (log) text length and maximum temperature, with random effects for year and each week (580 separate weeks, to try to control for topical issues).

Maximum temperature significantly improves the fit of the model over a null model with text length (Chi Squre = 23.7, df = 1, p < 0.00001).

Model estimates: 
                       Estimate Std. Error t value 
(Intercept)           4.100e-01  8.114e-04   505.3 
maxTempC.loc          9.628e-05  1.973e-05     4.9 5.340e-03  8.400e-04     6.4 

King uses proportionately more vowels when it’s warmer.  The effect is very small: On average, there is a difference of about 15 vowels used in an hour of conversation between summer and winter.  A model with location-specific maximum temperature improves the model fit over one with just LA-specific maximum temperature (Chi Sqaured = 11.59, df=1 , p=0.0007).

Of course, the temperature is not independent from day to day, so I also tried a lagged regression, predicting vowel ratio by text length (total) and maximum temperature of the recording location (maxTempC.loc).  Lagging back in time by days.

                          Estimate Std. Error t value Pr(>|t|) 
(Intercept)              4.076e-01  7.342e-04 555.073  < 2e-16 *** 
d[lag.0, ]$textLength    3.772e-07  6.715e-08   5.618 2.08e-08 *** 
d[lag.0, ]$maxTempC.loc  1.008e-04  3.300e-05   3.055  0.00227 ** 
d[lag.1, ]$maxTempC.loc  5.009e-05  3.812e-05   1.314  0.18893 
d[lag.2, ]$maxTempC.loc  1.549e-07  3.840e-05   0.004  0.99678 
d[lag.3, ]$maxTempC.loc -7.405e-05  3.809e-05  -1.944  0.05195 . 
d[lag.4, ]$maxTempC.loc -2.418e-06  3.300e-05  -0.073  0.94159 

The temperature of actual day is still significant, taking into account previous days.  Note that the coefficient is negative after 3 lagged days. (please forgive the rough analysis- it’s all I have left after my computer broke recently).

I’m not really sure what to make of this.  Given the data above, there is an argument that King is adapting the way he speaks to the climate.  However, a LOT more needs to be done in order to show this.  There are several confounding factors, such as the show being recorded in an air conditioned studio, the topics or guests might be different, there might be seasonal topics or key-words which affect the results (though one might argue that the lexicon for things related to cold climates has adapted).  The graphs show big jumps around week 32, which I can’t explain yet.  Then there is the question of the mechanism – how exactly is King adapting?  By choice of alternative words, or constructions?  And, of course, the transcripts are orthorgraphic.  And, of course, the idea is crazy.

Still, I think it’s amazing that we’re now in a position where we can even start asking these kind of questions with data.

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New experimental evidence of the effect of language on economic decisions

This is a guest post by Cole Robertson.

Readers of this blog are likely to be familiar with controversy surrounding Keith Chen’s (2013) findings suggesting that the way a language deals with the future tense affects speakers’ economic decisions. A new study by a group of Austrian and German economists has recently added experimental evidence to the growing body of research on the issue.

The study focuses on German and Italian. As with English, Italian requires a speaker to mark the future tense, e.g. “it will rain tomorrow” not simply “it rains tomorrow.” German, on the other hand, requires no such marking—speakers are free to say the equivalent of “it rains tomorrow.”

Chen hypothesized that speaking about future event using the present tense, as in languages like German, could make the future seem more immediate. He suggested this might cause speakers to value future events more highly than speakers of languages like Italian. Indeed, using large-scale statistical methods, Chen found that speakers of languages like German (with no separate future tense) tend to smoke less, be less obese, engage in safer sex practices, retire with more money, and save more per year.

His findings have been criticized on various grounds, from potential inconsistencies in the data, to small number bias in the original dataset, to the fact that the hypothesis could easily have been formulated the other way around, to the fact that Chen’s classification of how languages refer to the future may be overly simplistic.

However, most criticism has centred around the potential spuriousness of the correlation between future tense marking and future orientated behaviour. Commentators have been quick to point out that since cultural traits tend to be inherited in packages, it’s likely that future orientation and future tense reference are causally unrelated. In fact, Roberts, Winters and Chen (2015) found that the correlation dropped below significance when controlling for cultural relatedness (for some if not all their statistical tests). As such, the jury may yet be hung until experimental evidence confirms (or doesn’t) Chen’s findings.

The new study attempts to do exactly this. Though not yet peer reviewed, it was recently opened to comments and criticism as a discussion paper, as apparently is common in the discipline of economics.  You can read it here.

Meran / Merano / Maran

The paper takes advantage of bilingualism in the city of Meran in the autonomous province of South Tyrol in Northern Italy, where roughly 50% of the population speaks German and the other 50% speaks Italian. Hoping to mitigate the cultural confounds that plagued Chen’s (2013) findings, the authors argue that since the German- and Italian-speaking citizens of Meran share a home city, they also share a similar enough cultural milieu that experimenting on them can isolate the effects of their language on how they value future events.

The experiment worked like this: children were presented with three choices. In each of the choices they could either accept two tokens at the time of the test or opt instead to receive a greater number of tokens four weeks in the future (the ‘patient’ choice). The future rewards were three, four, or five tokens. So in other words, children had to choose three times, between: 1) two tokens now and three tokens in four weeks, 2) two tokens now and four tokens in four weeks, and 3) two tokens now and five tokens in four weeks.

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One of these choices was randomly selected for their actual pay-out, and they could then trade the tokens for a selection of small toys and items the experimenters had on offer. As control variables, they also measured IQ relative to cohort, the income and education of the parents, the children’s risk-taking propensity, average housing prices in the area of the school, and whether the children had friends who spoke another language.

In presenting their results they begin with a sample of just those students both of whose parents speak either German or Italian (n=860). They then progressively add students from different linguistic groups to their sample. They start with (n=203) students from bilingual German-Italian households, then add (n=261) students from household where both parents speak a language which has a future tense (like Italian) but which is not Italian. They then treat these delineations as categorical variables and use both regressions and non-parametric tests to see whether a child’s language category affects their tendency to wait for future rewards.

Their results suggest that it does. In the first sample, the German-speaking children were more likely to wait for the future reward than the Italian-speaking children, across all age groups and when including the host of control variables. Moreover, when they added the German-Italian bilingual group to the sample, their tendency to wait for future rewards was intermediate between the all-Italian and all-German children. Finally, they find that the (n=261) student who speak a language which marks the future tense, but which is not Italian, are significantly less likely to wait for future rewards compared to German speaking children, but are not significantly different from the Italian cohort.

They also separately analyse (n=91) students one of whose parents speak German or Italian and the other of whose parents (except for 5 cases) speaks a language which, like Italian, mandates marking of the future tense. They find that children with one German-speaking parent and one future-tense-marking parent are more likely to wait for future rewards than children with one Italian-speaking parent and another future-tense-marking parent.

Should these results be trusted? There are some strange statistics in the paper; throughout, they use multiple Mann-Whitney U Tests when comparing more than two groups, but never report any kind of post-hoc correction for multiple comparisons. With some p-values reported at the < .05 level, this could be problematic for some of their findings. Whilst their regressions would not be affected, I have to assume they present non-parametric tests because at least some of their data violate normality assumptions.

However, their results are corroborated by a second experiment which uses a slightly different discounting task and which only has two groups (all German and all Italian) and is therefore not affected by any apparent failure to correct for multiple comparisons.

They also include several other robustness tests. They make sure risk attitudes (which they find predict propensity to wait for future pay outs) are not correlated with language group (they aren’t). Although, whether this reveals anything more than their multiple regressions is unclear, since they already revealed a result whilst controlling for any correlation between the two variables. Additionally, they survey (n=177) Meraners to check whether there are any differences between the Italian and German populations in terms of their attitudes towards the importance of “thrift” and “patience.” Finding no such differences, they argue that this supports the conclusions that there are no cultural differences confounding their findings.

However, can we really trust self-reported estimations of the importance of thrift and patience? Most people know that they should say these are important, so is it really possible to rule out implicit demand characteristics that might undermine actual differences between the two language groups?

In fact, even according to the authors themselves, the German- and Italian-speaking populations in Meran remain linguistically and culturally “fairly segregated, with different media (like newspapers or TV channels) and leisure activities (like different football clubs)” (Sutter et al, 2015 p. 5). Schools are evidently also segregated by language, teaching either in Italian or German, and no schools to-date have an equal number of Italian and German students.

Indeed, relations between the Italian- and German-speaking people in South Tyrol may not be as copasetic as they are portrayed to be by the authors. In fact, there is evidence that tensions have been simmering since Mussolini attempted to “Italianise” the area in the 1930s by mass relocating Southern Italians northwards.  Activism in the 1960s (including violent conflict) eventually lead to a bilingual language accord, and significant autonomy from Rome in 1972. Today, German speakers accuse Italian authorities of racism and “linguistic imperialism”, whilst Italians accuse Germans of receiving preferential treatment. There have even been arguments over the language of signage on alpine hiking routes , which eventually sparked a felt-tipped graffiti war that quickly degenerated into racial profanity.  As such, is it really possible to rule out cultural confounds? As a Canadian who has lived in Montreal, the epicentre of Canadian French-English bilingual conflict, I can personally attest to the fact that geography and culture are not the same thing.

Moreover, the experiment does not actually manipulate children’s responses; it merely applies the same test to children from different language groups. What is strange is that there may actually be an unreported manipulation in the experiment. Since the authors only state that the test prompts were given in the child’s “mother tongue”, I would assume that some of the (n=203) bilingual children were tested in Italian and some in German. This means that the researchers hopefully have (or might be able to get) data on whether the language of the test prompt affected the children’s propensity to wait for future rewards.

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Until they include these results in the analysis, their findings seem to be subject to the same criticisms levelled against Chen (2013). In other words, they may be picking up on a spurious correlation resulting from the fact that thriftiness and tense structure, whilst causally unrelated, could have been co-inherited from antecedent cultural groups.

If the Italian and German populations in South Tyrol are as alienated and segregated as they seem to be, it’s entirely possible that the German-speakers inherited increased thriftiness as well as a language without a future tense, whilst the Italian-speakers inherited decreased thriftiness as well as a language with a future tense. They need not be causally related, and the speakers’ geographical proximity may not have been enough to override these packages of traits. Until we see a language-based manipulation of future-orientated behaviour, the issue of whether tense affects how we value future events will remain unresolved.


Chen, M. K. (2013). “The Effect of Language on Economic Behavior: Evidence from Savings Rates, Health Behaviors, and Retirement Assets.” American Economic Review 103(2): 690-731.

Roberts, S. G., Winters, J. & Chen, M. K. (2015). “Future Tense and Economic Decisions: Controlling for Cultural Evolution.” PLoS One 10(7): e0132145.

Sutter, M., et al. (2015). “The Effect of Language on Economic Behavior: Experimental Evidence from Children’s Intertemporal Choices.” IZA Discussion Paper Series 9383.

cole faceshotCole Robertson lives and works in Oxford, where he is completing a PhD focusing on inter-linguistic tense differences and future-orientated behavior, but he’s generally interested in how language interfaces with other cognitive, perceptual, and behavioural systems, as well as language revitalization and language evolution. He’s an avid rock climber and mountaineer and once spent two days eating nothing but sausages cooked over a candle whilst waiting out a storm. He grew up in Vancouver, Canada.

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CreaStoria: Experimenting with collaborative stories

This is a guest post by Christine Cuskley

TL;DR: Please and thank you play this thing for science.

Insofar as the field of language evolution has even had time to spill a lot of ink about anything – if you take Pinker & Bloom’s seminal 1990 paper as the starting point, the field is only just a carefree twenty-something – the focus of the field has primarily been about the finer points of language: syntax, the lexicon, the physiology of speech production, etc. But one’s mid-twenties are a time for exploration, so, with my colleagues at the Social Dynamics Unit, we’re looking towards something relatively unexplored in language evolution: stories.

It’s almost impossible to imagine telling a story without language – how would you even begin? (Even Emoji Dick had to be translated from the original, and might not even be successful, and emojis arguably are language…but I digress…) So the questions emerge: why and how do we tell stories? Do stories simply take advantage of our ability to speak about things that are not present and/or are not concrete (or even real), or are they a key part in how language evolved the ability to do this? How do stories evolve over time and respond to cultural pressures? What kinds of features of stories survive and replicate, and what features peter off and die? What selection pressures underlie this?

This is, of course a whole host of questions, none of which we can expect to find definitive answers to anytime soon – a feature shared by a lot of work in language evolution (and an exciting one, in my opinion). And of course, we’re not jumping into a void: already there is work that focuses on the phylogeny of stories, the potential evolutionary function of stories, and also a fair bit of work on evolution in literature more generally, some of it featured right here on Replicated Typo. But we’re taking a new experimental approach: we’re crowd sourcing collaborative stories. We hope this will contribute to answering the last two questions in particular: how do stories evolve over time and respond to different constraints, and what features survive and replicate?

We’re doing this using an experimental game called CreaStoria – and the more players we have, the better! So please play! The game is a hybrid of choose your own adventure, Twitter, and a creative writing workshop. It works like this: we start with a bunch of single-sentence “story prompts” created in collaboration with Piano Piano Book Bakery in Rome, and these stories become the “root” for collaborative story trees. At each turn, a player is presented with three potential stories and has to choose which one to continue with their own short story, creating an element of preferential selection. After you’ve played, or between bouts of play (I hear it’s great for procrastination, so feel free to come and go as you need it), you can look at the growing story tree and vote on stories you like (or don’t).

The inner workings are a bit more complicated than this, of course – I could tell you, but I’d have to “know your IP address and exclude any stories you write from our data” (if you know what I mean). We’ve had the opportunity to exhibit the game at a couple of live events in Italy, so the tree of Italian stories is pretty well populated – but we would really like more English data (and having a lot of both could lead to some interesting contrasts), so play now and tell your friends! If you’re curious as to how the data pans out, like the game on Facebook or follow @creastoria on Twitter to get updates.

Happy writing!

Christine Cuskley is a linguist/psychologist/nerd type who currently researches the evolution of language and communication in the Social Dynamics Unit at the Institute for Scientific Interchange in Turin, Italy, and will take up a position as a British Academy Postdoctoral Fellow at the University of Edinburgh from January 2016. She mostly retweets at @nerdpro.


Dennett on Memes, Neurons, and Software

Another working paper, links:

Abstract, contents, and introduction below.

* * * * *

Abstract: In his work on memetics Daniel Dennett does a poor job of negotiating the territory between philosophy and science. The analytic tools he has as a philosopher aren’t of much use in building accounts of the psychological and social mechanisms that underlie cultural processes. The only tool Dennett seems to have at his disposal is analogy. That’s how he builds his memetics, by analogy from biology on the one hand and computer science on the other. These analogies do not work very well. To formulate an evolutionary account of culture one needs to construct one’s gene and phenotype analogues directly from the appropriate materials, neurons and brains in social interaction. Dennett doesn’t do that. Instead of social interaction he has an analogy to apps loading into computers. Instead of neurons he has homuncular agents that are suspiciously like his other favorite homuncular agents, memes. It doesn’t work.


Introduction: Too many analogies, no construction 2
Watch Out, Dan Dennett, Your Mind’s Changing Up on You! 5
The Memetic Mind, Not: Where Dennett Goes Wrong 11
Turtles All the Way Down: How Dennett Thinks 16
A Note on Dennett’s Curious Comparison of Words and Apps 21
Has Dennett Undercut His Own Position on Words as Memes? 23
Dennet’s WRONG: the Mind is NOT Software for the Brain 27
Follow-up on Dennett and Mental Software 31

Introduction: Too many analogies, no construction

Just before the turn of the millennium Dennet gave an interview in The Atlantic in which he observed:

In the beginning, it was all philosophy. Aristotle, whether he was doing astronomy, physiology, psychology, physics, chemistry, or mathematics — it was all the same. It was philosophy. Over the centuries there’s been a refinement process: in area after area questions that were initially murky and problematic became clearer. And as soon as that happens, those questions drop out of philosophy and become science. Mathematics, astronomy, physics, chemistry — they all started out in philosophy, and when they got clear they were kicked out of the nest.

Philosophy is the mother. These are the offspring. We don’t have to go back a long way to see traces of this. The eighteenth century is quite early enough to find the distinction between philosophy and physics not being taken very seriously. Psychology is one of the more recent births from philosophy, and we only have to go back to the late nineteenth century to see that.

My sense is that the trajectory of philosophy is to work on very fundamental questions that haven’t yet been turned into scientific questions.

This is a standard view, and it’s one I hold myself, though it’s not clear to me just how it would look when the historical record is examined closely.

But I do think that, in his recent work, Dennett’s been having troubles negotiating the difference between philosophy, in which he has a degree, and science. For he is also a cognitive scientist in good standing, and that phrase – “cognitive science” – stretches all over the place, leaving plenty of room to get tripped up over the difference between philosophy and science.

Dennett has spent much of his career as a philosopher of artificial intelligence, neuroscience, and cognitive psychology. That is to say, he’s looked at the scientific work in those disciplines and considered philosophical implications and foundations. More recently he’s done the same thing with biology.

Now, it is one thing to apply the analytic tools of philosophy to the fruits of those disciplines. But Dennett has also been interested in memetics, a putative evolutionary account of culture. The problem is that there is no science of memetics for Dennett to analyze. So, when he does memetics, just what is he doing?

The analytic tools he has as a philosopher aren’t of much use in building accounts of the psychological and social mechanisms that might underlie cultural processes. The only tool Dennett seems to have at his disposal is analogy. And so that’s how he builds his memetics, by analogy from biology on the one hand and computer science on the other.

Alas, these analogies do not work very well. That’s what I examine in the posts I’ve gathered into this working paper. What Dennett, or anyone else, needs to do to formulate an evolutionary account of culture is to construct one’s gene and phenotype analogues (if that’s what you want to do) directly from the appropriate materials, neurons and brains in social interaction. Dennett doesn’t do that. Instead of social interaction he has an analogy to apps loading into computers. Instead of neurons he has homuncular agents that are suspiciously like his other favorite homuncular agents, memes. It doesn’t work. It’s incoherent. It’s bad philosophy or bad science, or both. Continue reading

Posture helps robots learn words, and infants, too.

What kind of information do children and infants take into account when learning new words? And to what extent do they need to rely on interpreting a speakers intention to extract meaning? A paper by Morse, Cangelosi and Smith (2015), published in PLoS One, suggests that bodily states such as body posture might be used by infants to acquire word meanings in the absence of the object named. To test their hypothesis, the authors ran a series of experiments using a word learning task with infants—but also a self-learning robot, the iCub.

Continue reading


International Association for Cognitive Semiotics (IACS 2016)

Call for papers for the Second Conference of the
International Association for Cognitive Semiotics (IACS 2016)
June 20-22, 2016
Maria Curie-Sklodowska University, Lublin, Poland

Plenary speakers confirmed up to now:

Cognitive Semiotics as a field of study deals with questions concerning the nature of meaning as well as the role of consciousness, the unique cognitive features of human beings, the interaction of nature and nurture in development, and the interplay of biological and cultural evolution in phylogeny. To answer these questions CS integrates methods and theories developed in the human and social sciences as well as cognitive sciences. TheInternational Association for Cognitive Semiotics (IACS, founded 2013) aims at the establishment of Cognitive Semiotics as the trans-disciplinary study of meaning. More information on the International Association for Cognitive Semiotics can be found at:

One of the goals of the IACS conference series is to gather together scholars and scientists in semiotics, linguistics, philosophy, cognitive science, psychology and related fields, who wish to share their research on meaning and contribute the interdisciplinary dialogue

Topics of the conference include (but are not limited to):

  • Biological and cultural evolution of human cognitive specificity
  • Cognitive linguistics and phenomenology
  • Communication across cultural barriers
  • Cross-species comparative semiotics
  • Evolutionary perspectives on altruism
  • Experimental semiotics
  • Iconicity in language and other semiotic resources
  • Intersubjectivity and mimesis in evolution and development
  • Multimodality
  • Narrativity across different media
  • Semantic typology and linguistic relativity
  • Semiosis (sense-making) in social interaction
  • Semiotic and cognitive development in children
  • Sign use and cognition
  • Signs, affordances, and other meanings
  • Speech and gesture
  • The comparative semiotics of iconicity and indexicality
  • The evolution of language

We invite abstract submissions for theme sessions, oral presentations and posters (please clearly indicate your chosen format with your submission)

Submission guidelines and formats:

1. Theme sessions (deadline: 30 Nov 2015)
– submission should include: session title, name and affiliation of symposium convener, an introduction of up to 400 words explaining the theme, all symposium abstracts, in suitable order
– sessions may consist of of 3-5 papers (90-150 min.), allowing time for general discussion. Papers in each theme session should be thematically linked
*)Theme session proposers should indicate whether, if a session is not accepted as a whole, they wish the individual abstracts to be considered as individual presentations (oral or poster)

2. Oral presentations (deadline: 10 Jan 2016)
submission should include: title, name, affiliation, 400 word abstract
20 min presentation followed by 7 min. discussion

3. Posters (deadline: 10 Jan 2016)
submission should include: title, name, affiliation, 100 word abstract
1 minute oral presentation in the main lecture hall, preceding the poster session

Abstracts should be submitted as .odt, .doc or .docx attachments using EasyChair: In order to submit an abstract you have to use your existing EasyChair account or register using the link above. Detailed instructions can be found on the IACS 2016 conference website:

In the case of questions or doubts do not hesitate to contact the Organizers: iacs2016[at]

Important dates:

  • Deadline for submission of theme sessions: 30 Nov 2015
  • Deadline for abstract submission (oral presentations, posters): 10 Jan 2016
  • Notification of acceptance (oral presentations, posters): 29 Feb 2016
  • Last date for early registration: 15 Apr 2016



Videos from the The Evolution of Phonetic Capabilities Satellite Event

This year, as part of the International Congress of Phonetic Sciences, I hosted a satellite event about the evolution of speech.

Here’s the preamble:

In recent years, there has been a resurgence in research in the evolution of language and speech. New techniques in computational and mathematical modelling, experimental paradigms, brain and vocal tract imaging, corpus analysis and animal studies, as well as new archeological evidence, have allowed us to address questions relevant to the evolution of our phonetic capabilities. The workshop will focus on recent work addressing the emergence of our phonetic capabilities, with a special focus on the interaction between biological and cultural evolution.

And here’s the meeting, in video form, should anyone have regretted missing it, or wanted to watch the talks again!

Here’s the play order:

  1. John H. Esling, Allison Benner & Scott R. Moisik – Laryngeal Articulatory Function and Speech Origins

2.  Scott R. Moisik & Dan Dediu – Anatomical biasing and clicks: Preliminary biomechanical modeling

3. Seán G. Roberts, Caleb Everett & Damián Blasi  – Exploring potential climate effects on the evolution of human sound systems

4. Padraic Monaghan & Willem H. Zuidema – General purpose cognitive processing constraints and phonotactic properties of the vocabulary

5. Bodo Winter & Andy Wedel – Simulating the interaction of functional pressure, redundancy and category variation in phonetic systems

6. Bill Thompson – Universality in Cultural Transmission

Universal Principles in the Repair of Communication Problems

Yesterday, my colleagues and I published a paper on Universal Principles in the Repair of Communication Problems.

People are constantly having problems with communication, like these two people:

In this paper, a team of linguists looked at over 2000 cases of problems with communication in 12 languages.  On average, people have a problem with understanding every 90 seconds! The team coded each instance and found that the same 3 basic tools were used in each language:

  • Open Request: Signalling a problem with the whole utterance (Huh?)
  • Restricted Request: Asking for clarification of a part (Go where?)
  • Restricted Offer: Asking for confirmation of what was heard (Go between them?)

Each tool is increasingly specific about the source of the problem, but takes longer on average to produce.  This means that the amount of work to repair the problem is shared between the speakers.  We can see this in the following graph:  The more I contribute to repair in initiation, the less you have to contribute in response:


We also found that, on average, a problem takes about as long to repair as it did to produce, regardless of type.

What this suggests is that people have a pro-social bias.  In principle, any problem can be fixed with the easy-to-produce huh?  So if people were being selfish, they might just produce this all the time.  However,  each langauge uses each type, which suggests that listeners try to help out as much as they can:  speakers treat conversation as a joint activity and try to work together to fix problems.

We found some variation between languages in the proportion of repair types used.  However, we also found that the same factors which cause problems (e.g. noise, parallel activities) affected which tool was chosen in the same way across all languages.   That is, the repair system works in the same way for all languages.

This was tested using a mixed effects model which controlled for the shared history between languages.  Specifically, we show that knowing what language was being spoken does not help predict what type of repair was used, over and above factors which cause problems.  I’m quite proud of this mix of qualitative coding, quantitative measures and statistical methods.  With 12 authors from 6 institutions, it’s also a great example of collaborative science.  12 languages may not seem like much compared to typological studies of language structure, but it has to be kept in mind that the instances come from recordings of ordinary conversations which are then transcribed, translated and coded (48 hours of video in total!).  The languages are also far from a convenience sample, ranging from Yeli Dyne in Papua to Argentine Sign Language.

As far as we know, no other species has this kind of sophisticated set of tools for solving communication problems.  In fact, even basic repair seems to be unique to humans.  We suggest, then, that this system of repair is a universal principle of human communication which emerges from a need to be understood in a noisy world.

You can read the paper here, and some more details on the ideophone blog.

Culture, its evolution and anything inbetween