CfP: Measuring Language Complexity at EvoLang

This is a guest post from Aleksandrs Berdicevskis about the workshop Measuring Language Complexity.

A lot of evolutionary talks and papers nowadays touch upon language complexity (at least nine papers did this at the Evolang 2016). One of the reasons is probably that complexity is a very convenient testbed for testing hypotheses that establish causal links between linguistic structure and extra-linguistic factors. Do factors such as population size, or social network structure, or proportion of non-native speakers shape language change, making certain structures (for instance, those that are morphologically simpler) more evolutionary advantageous and thus more likely? Or don’t they? If they do, how exactly?

Recently, quite a lot has been published on that topic, including attempts to do rigorous quantitative tests of the existing hypotheses. One problem that all such attempts face is that complexity can be understood in many different ways, and operationalized in yet many more. And unsurprisingly, the outcome of a quantitative study depends on what you choose as your measure! Unfortunately, there currently is little consensus about how measures themselves can be evaluated and compared.

To overcome this, we organize a shared task “Measuring Language Complexity”, a satellite event of Evolang 2018, to take place in Torun on April 15. Shared tasks are widely used in computational linguistics, and we strongly believe they can prove useful in evolutionary linguistics, too. The task is to measure the linguistic complexity of a predefined set of 37 language varieties belonging to 7 families (and then discuss the results, as well as their mutual agreement/disagreement at the workshop). See the detailed CfP and other details here.

So far, the interest from the evolutionary community has been rather weak. But there is still time! We extended the deadline until February 28 and are looking forward to receiving your submissions!

CfP: Applications in Cultural Evolution, June 6-8, Tartu

Guest post by Peeter Tinits and Oleg Sobchuk
As mentioned in this blog before, evolutionary thinking can help the study of various cultural practices, not just language. The perspective of cultural evolution is currently seeing an interesting case of global growth and coordination – the widely featured founding of the Cultural Evolution Society (also on replicatedtypo), the recent inaugural conference and follow-ups are bringing a diverse set of researchers around the same table. If this has gone past you unnoticed – there’s nice resourcesgathered on the society website.
Evolutionary thinking seems useful for various purposes. However does it work the same everywhere, and can research progress in one domain be easily carried over to another?
To make better sense of it, we’re organizing a small conference to discuss the ways that evolutionary thinking can be best applied in different domains. The event “Applications in Cultural Evolution: Arts, Languages, Technologies” is to take place in June 6-8 in Tartu, Estonia. Pleanary speakers include:
We  invite contributions from cultural evolution researchers of various persuasions and interests to talk about their work and how the evolutionary models help with that. Deadline for abstracts on Feb 14.
Discussion of individual contributions will hopefully lead to a better understanding of commonalities and differences in how cultural evolution is applied in different areas, and help build an understanding of how to most productively use evolutionary thinking – what are the prospects and limitations. We aim to allow for building a common ground through plenty of space and opportunities for formal and informal discussion on site.
Both case studies and general perspectives welcome. In addition to original research we encourage participants to think of the following questions:
– What do you get out of cultural evolution research?
– How should we best apply evolutionary thinking to culture?
– What matters when we apply this to different domains or timescales?
Deadline for abstracts: February 14, 2018
Event dates: June 6-8
Location: Tartu University, Estonia
Full call for papers and information on the website. Also available as PDF.

Deadline extended for Triggers of Change in the Language Sciences

The deadline for the 2nd XLanS conference on Triggers of Change in the Language Sciences has extended its submission deadline to June 14th.

This year’s topic is ‘triggers of change’:  What causes a sound system or lexicon or grammatical system to change?  How can we explain rapid changes followed by periods of stability?  Can we predict the direction and rate of change according to external influences?

We have also added two new researchers to our keynote speaker list, which now stands as:

 

Wh-words sound similar to aid rapid turn taking

A new paper by Anita Slonimska and myself attempts to link global tendencies in the lexicon to constraints from turn taking in conversation.

Question words in English sound similar (who, why, where, what …), so much so that this class of words are often referred to as wh-words. This regularity exists in many languages, though the phonetic similarity differs, for example:

English Latvian Yaqui Telugu
haw ka: jachinia elaa
haw mɛni tsik jaikim enni
haw mətʃ tsik jaiki enta
wət kas jita eem;eemi[Ti]
wɛn kad jakko eppuDu
wɛr kuɾ jaksa eTa; eedi; ekkaDa
wɪtʃ kuɾʃ jita eevi
hu kas jabesa ewaru
waj ˈkaːpeːts jaisakai en[du]ceeta; enduku

In her Master’s thesis, Anita suggested that these similarities help conversation flow smoothly.  Turn taking in conversation is surprisingly swift, with the usual gap between turns being only 200ms.  This is even more surprising when one considers that the amount of time it takes to retrieve, plan and begin pronouncing one word is 600ms.  Therefore, speakers must begin planning what they will say before current speaker has finished speaking (as demonstrated by many recent studies, e.g. Barthel et al., 2017). Starting your turn late can be interpreted as uncooperative, or lead to missing out on a chance to speak.

Perhaps the harshest environment for turn-taking is answering a content question.  Responders must understand the question, retrieve the answer, plan their utterance and begin speaking.  It makes sense to expect that cues would evolve to help responders recognise that a question is coming.  Indeed there are many paralinguistic cues, such as rising intonation (even at the beginning of sentences) and eye gaze.  Another obvious cue is question words, especially when they appear at the beginning of question sentences. Slonimska hypothesised that wh-words sound similar in order to provide an extra cue that a question is about to be asked, so that the speaker can begin preparing their turn early.

We tried to test this hypothesis, firstly by simply asking whether wh-words really do have a tendency to sound similar within languages.  We combined several lexical databases to produce a word list for 1000 concepts in 226 languages, including question words.  We found that question words are:

  • More similar within languages than between languages
  • More similar than other sets of words (e.g. pronouns)
  • Often composed of salient phonemes

Of course, there are several possible confounds, such as languages being historically related, and many wh-words being derived from other wh-words within a language. We attempted to control for this using stratified permutation, excluding analysable forms, and comparing wh words to many other sets of words such as pronouns which are subject to the same processes.  Not all languages have similar-sounding wh-words, but across the whole database the tendancy was robust.

Another prediction is that the wh-word cues should be more useful if they appear at the beginning of question sentences.  We tested this using typological data on whether wh-words appear in initial position.  While the trend was in the right direction, the result was not significant when controlling for historical and areal relationships.

Despite this, we hope that our study shows that it is possible to connect constraints from turn taking to macro-level patterns across languages, and then test the link using large corpora and custom methods.

Anita will be presenting an experimental approach to this question at this year’s CogSci conference.  We show that /w,h/ is a good predictor of questions in real English conversations, and that people actually use /w,h/ to help predict that a question is coming up.

Slonimska, A., & Roberts, S. G. (2017). A case for systematic sound symbolism in pragmatics: Universals in wh-words. Journal of Pragmatics, 116, 1-20. ArticlePDF.

All data and scripts are available in this github repository.

Iconicity evolves by random mutation and biased selection

A new paper by Monica Tamariz, myself, Isidro Martínez and Julio Santiago uses an iterated learning paradigm to investigate the emergence of iconicity in the lexicon.  The languages were mappings between written forms and a set of shapes that varied in colour, outline and, importantly, how spiky or round they were.

We found that languages which begin with no iconic mapping develop a bouba-kiki relationship when the languages are used for communication between two participants, but not when they are just learned and reproduced.  The measure of the iconicity of the words came from naive raters.

Here’s one of the languages at the end of a communication chain, and you can see that the labels for spiky shapes ‘sound’ more spiky:

An example language from the final generation of our experiment: meanings, labels and spikiness ratings.

These experiments were actually run way back in 2013, but as is often the case, the project lost momentum.  Monica and I met last year to look at it again, and we did some new analyses.  We worked out whether each new innovation that participants created increased or decreased iconicity.  We found that new innovations are equally likely to result in higher or lower iconicity: mutation is random.  However, in the communication condition, participants re-used more iconic forms: selection is biased.  That fits with a number of other studies on iconicity, including Verhoef et al., 2015 (CogSci proceedings) and Blasi et al. (2017).

Matthew Jones, Gabriella Vigliocco and colleagues have been working on similar experiments, though their results are slightly different.  Jones presented this work at the recent symposium on iconicity in language and literature (you can read the abstract here), and will also present at this year’s CogSci conference, which I’m looking forward to reading:

Jones, M., Vinson, D., Clostre, N., Zhu, A. L., Santiago, J., Vigliocco, G. (forthcoming). The bouba effect: sound-shape iconicity in iterated and implicit learning. Proceedings of the 36th Annual Meeting of the Cognitive Science Society.

Our paper is quite short, so I won’t spend any more time on it here, apart from one other cool thing:  For the final set of labels in each generation we measured iconicity using scores from nieve raters, but for the analysis of innovations we had hundreds of extra forms.  We used a random forest to predict iconicity ratings for the extra labels from unigrams and bigrams of the rated labels.  It accounted for 89% of the variance in participant ratings on unseen data.  This is a good improvement over some old techniques such as using the average iconicity of the individual letters in the label, since random forests allows the weighting of particular letters to be estimated from the data, and also allows for non-linear effects when two letters are combined.

However, it turns out that most of the prediction is done by this simple decision tree with just 3 unigram variables. Shapes were rated as more spiky if they contained a ‘k’, ‘j’ and ‘z’ (our experiment was run in Spanish):

So the method was a bit overkill in this case, but might be useful for future studies.

All data and code for doing the analyses and random forest prediction is available in the supporting information of the paper, or in this github repository.

Tamariz, M., Roberts, S. G., Martínez, J. I. and Santiago, J. (2017), The Interactive Origin of Iconicity. Cogn Sci. doi:10.1111/cogs.12497[pdf from MPI]

Biggest linguistics experiment ever links perception with linguistic history

Back in March 2014, Hedvig Skirgård and I wrote a post about the Great Language Game.  Today we’ve published those results in PLOS ONE, together with the Game’s creator Lars Yencken.

One of the fundamental principles of linguistics is that speakers that are separated in time or space will start sound different, while speakers who interact with each other will start to sound similar.  Historical linguists have traced the diversification of languages using objective linguistic measurements, but so far there has never been a widespread test of whether languages further away on a family tree or more physically distant from each other actually sound different to human listeners.

An opportunity arose to test this in the form of The Great Language Game: a web-based game where players listen to a clip of someone talking and have to guess which language is being spoken.  It was played by nearly one million people from 80 countries, and so is, as far as we know, the biggest linguistic experiment ever.  Actually, this is probably my favourite table I’ve ever published (note the last row):

Continent of IP-address Number of guesses
Europe 7,963,630
North America 5,980,767
Asia 841,609
Oceania 364,390
South America 356,390
Africa 74,032
Antarctica 11

We calculated the probability of confusing any of the 78 languages in the Great Language Game for any of the others (excluding guesses about a language if it was an official language of the country the player was in).  Players were good at this game – on average getting 70% of guesses correct.

Using partial Mantel tests, we found that languages are more likely to be confused if they are:

  • Geographically close to each other;
  • Similar in their phoneme inventories
  • Similar in their lexicon
  • Closely related historically (but this effect disappears when controlling for geographic proximity)

We also used Random Forests analyses to show that a language is more likely to be guessed correctly if it is often mentioned in literature, is the main language of an economically powerful country, is spoken by many people or is spoken in many countries.

We visualised the perceptual similarity of languages by using the inverse probability of confusion to create a neighbour net:

This diagram shows a kind of subway map for the way languages sound. The shortest route between two languages indicates how often they are confused for one another – so Swedish and Norwegian sound similar, but Italian and Japanese sound very different. The further you have to travel, the more different two languages sound.  So French and German are far away from many languages, since these were the best-guessed in the corpus.

The labels we’ve given to some of the clusters are descriptive, rather than being official terms that linguists use.  The first striking pattern is that some languages are more closely connected than others, for example the Slavic languages are all grouped together, indicating that people have a hard time distinguishing between them. Some of the other groups are more based on geographic area, such as the ‘Dravidian’ or ‘African’ cluster. The ‘North Sea’ cluster is interesting: it includes Welsh, Scottish Gaelic, Dutch, Danish, Swedish, Norwegian and Icelandic.  These diverged from each other a long time ago in the Indo-European family tree, but have had more recent contact due to trade and invasion across the North Sea.

The whole graph splits between ‘Western’ and ‘Eastern’ languages (we refer to the political/cultural divide rather than any linguistic classification). This probably reflects the fact that most players were Western, or at least could probably read the English website.  That would certainly explain the linguistically confused “East Asian” cluster.  There are also a lot of interconnected lines, which indicates that some languages are confused for multiple groups, for example Turkish is placed halfway between “West” and “East” languages.

It was also possible to create neighbour nets for responses from specific parts of the world. While the general pattern is similar, there are also some interesting differences.  For example, respondents from North America were quite likely to confused Yiddish and Hebrew.  They come from different language families, but are spoken by a mainly Jewish population and this may form part of players’ cultural knowledge of these languages.

In contrast, players from African placed Hebrew with the other Afro-Asiatic languages.

Results like this suggest that perception may be shaped by our linguistic history and cultural knowledge.

We also did some preliminary analyses on the phoneme inventories of languages, using a binary decision tree to explore which sounds made a language distinctive.  Binary decision trees identified some rare and salient features as critical cues to distinctiveness.

The future

http://is5.mzstatic.com/image/thumb/Purple69/v4/bd/32/7d/bd327d24-f55c-b340-2f89-511ccf7ab870/source/175x175bb.jpg

The analyses were complicated because we knew little about the individuals playing beyond the country of their IP address.  However, Hedvig and I, together with a team from the Language in Interaction consortium (Mark Dingemanse, Pashiera Barkhuysen and Peter Withers) create a version of the game called LingQuest that does collect people’s linguistic background.  It also asks participants to compare sound files directly, rather than use written labels.

You can download LingQuest as an apple App, or play it online here.

 

 

 

Conference: Triggers of change in the language sciences

The University of Lyon 2 is proud to announce ‘Triggers of Language Change in the Language Sciences’.

October 11th-14th 2017, University of Lyon, France.

See the website for our call for papers and further details.

The conference is part of the “X in the Language Sciences” (XLanS) series which aims to bring a wide range of researchers together to focus on a particular topic in language that interests them.  The goal is to identify the crucial issues and connect them with cutting-edge techniques in order to develop better explanations of linguistic phenomena (see details of the first conference “Causality in the language sciences” here).

This year’s topic is ‘triggers of change’:  What causes a sound system or lexicon or grammatical system to change?  How can we explain rapid changes followed by periods of stability?  Can we predict the direction and rate of change according to external influences?

Our keynote speakers include:
Michael C. Gavin (Colorado State University)
Monica Tamariz (Heriot Watt University)
Sarah Thomason (University of Michigan)
Brigitte Pakendorf (University of Lyon)
Alan Yu (University of Chicago)
We are pleased to be able to offer scholarships to cover travel for students from the developing world and reduced rates for lower-income attendees.  See the Registration Details page for details.

The XLanS committee,

Christophe Coupé, Damián Blasi, Dan Dediu, Hedvig Skirgård, Julia Uddén, Seán Roberts

Women in Language Evolution

It’s International Women’s day!  Language Evolution is a largely male dominated discipline: women account for only 8 out of the top 100 most cited authors, and only 14 out of 82 invited speakers at the Evolution of Language Conference (see here).  To promote the contribution of women to our field, we’ve compiled a list of 100 female researchers in language evolution.

The list is by no means exhaustive, and is largely based on attendance at the most recent EvoLang conference.  Topics cover both language origins and evolutionary approaches to linguistics more generally.  A recent paper by each author is also included, though it may not be the best representation of their work.  All mistakes with regards to links and citations are my own.

 

Adele E. Goldberg

Goldberg, A. E. (2015). Subtle implicit language facts emerge from the functions of constructions. Frontiers in psychology, 6.

Alexandra Carstensen

Regier, T., Carstensen, A., & Kemp, C. (2016). Languages support efficient communication about the environment: words for snow revisited. PloS one, 11(4), e0151138.

Amy Bauernfeind

Bauernfeind AL, Soderblom EJ, Turner ME, Moseley MA, Ely JJ, Hof PR, Sherwood CC, Wray GA, Babbitt CC. Evolutionary divergence of gene and protein expression in the brains of humans and chimpanzees. Genome Biology and Evolution. doi: 10.1093/gbe/evv132

Amy Perfors

A Perfors (in press). On simplicity and emergence: Commentary on Johnson (2016) Psychonomic Bulletin and Review: Special issue on language evolution

Andrea Claude

Calude, A & Verkerk, A. (2016). How to build the Number Line in Indo-European – a Phylogenetic Study. Journal of Language Evolution [link]

Andreea Geambasu

Geambașu A., Ravigniani A. & Levelt C.C. (2016), Preliminary Experiments on Human Sensitivity to Rhythmic Structure in a Grammar with Recursive Self-Similarity, Frontiers in Neuroscience 10.

Anna Jon-And

Jon-And (2016) Modeling language change triggered by language shift. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Anna Maria Di Sciullo

Sciullo (2016) Emergent syntax and syntactic variation. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Anne Kandler

Kandler, A., Wilder, B., & Fortunato, L. (2017). Inferring individual-level processes from population-level patterns in cultural evolution. bioRxiv, 111575.

Annemarie Verkerk

Calude, A & Verkerk, A. (2016). How to build the Number Line in Indo-European – a Phylogenetic Study. Journal of Language Evolution [link]

Anu Vastenius

(2016) Constituent order in pictorial representations of events is influenced by language. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Ashley Micklos

Micklos (2016) Interaction for facilitating conventionalization: negotiating the silent gesture communication of noun-verb pairs. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Asifa Majid

Majid, A., Jordan, F., & Dunn, M. (2015). Semantic systems in closely related languages.

Brenda McCowan

Beisner, B. A., Hannibal, D. L., Finn, K. R., Fushing, H., & McCowan, B. (2016). Social power, conflict policing, and the role of subordination signals in rhesus macaque society. American journal of physical anthropology.

Bridget Samuels

Samuels, B. D. (2015). Can a bird brain do phonology?. Frontiers in psychology, 6.

Brigitte Pakendorf

Pakendorf, B. (2014). Coevolution of languages and genes. Current opinion in genetics & development, 29, 39-44.

Buddhamas Kriengwatana

Kriengwatana (2016) A general auditory bias for handling speaker variability in speech? evidence in humans and songbirds. . The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Camilla Power

Power, C., Finnegan, M., & Callan, H. (2016). Human Origins: Contributions from Social Anthropology.

Carmen Saldana

(2016) The cultural evolution of complexity in linguistic structure. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Carol Padden

Padden, C., Meir, I., Aronoff, M. and Sandler, W. (in press) The grammar of space in two new sign languages. In D. Brentari (Ed.), Sign Languages: A Cambridge Survey. New York: Cambridge University Press.

Catherine Hobaiter

Hobaiter, C., Poisot, T., Zuberbühler, K., Hoppitt, W., & Gruber, T. (2014). Social network analysis shows direct evidence for social transmission of tool use in wild chimpanzees. PLoS Biol, 12(9), e1001960.

Catriona Silvey

Silvey, C., Kirby, S., & Smith, K. (2015). Word meanings evolve to selectively preserve distinctions on salient dimensions. Cognitive Science, 39(1), 212-226.

Cecilia Heyes

Heyes, C. (2016). Blackboxing: social learning strategies and cultural evolution. Phil. Trans. R. Soc. B, 371(1693), 20150369.

Chiara Barbieri

Barbieri, C., Güldemann, T., Naumann, C., Gerlach, L., Berthold, F., Nakagawa, H., … & Pakendorf, B. (2014). Unraveling the complex maternal history of Southern African Khoisan populations. American journal of physical anthropology, 153(3), 435-448.

Christina Behme

Behme, C. (2015). Is the ontology of biolinguistics coherent?. Language Sciences, 47, 32-42.

Christine Caldwell

Caldwell CA, Atkinson M & Renner E (2016) Experimental approaches to studying cumulative cultural evolution, Current Directions in Psychological Science, 25 (3), pp. 191-195.

Christine Cuskley

Cuskley, C., Simner, J. and Kirby, S. (2015). Phonological and orthographic influences in the bouba-kiki effect. Psychological Research, doi: 10.1007/s00426-015-0709-2.

Claire Bowern

Bowern, C. (2015). Linguistics: Evolution and Language Change. Current Biology, 25(1), R41-R43.

Colleen Reichmuth

Reichmuth, C., & Casey, C. (2014). Vocal learning in seals, sea lions, and walruses. Current opinion in neurobiology, 28, 66-71.

Cory Cuthbertson

(2016) Empirically assessing linguistic ability with stone tools. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Dean Falk

Falk, D. (2016). Evolution of Brain and Culture. Journal of Anthropological Sciences, 94, 1.

Deborah Kerr

(2016) The spontaneous emergence of linguistic diversity in an artificial language. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Dedre Gentner

Gentner, D. (2016). Language as cognitive tool kit: How language supports relational thought. American Psychologist, 71(8), 650.

Diane Reiss

Maust-Mohl, M., Soltis, J., & Reiss, D. (2015). Acoustic and behavioral repertoires of the hippopotamus (Hippopotamus amphibius). The Journal of the Acoustical Society of America, 138(2), 545-554.

Ekaterina Abramova

(2016) Triadic ontogenetic ritualization: an overlooked possibility. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Elizabeth Irvine

Irvine (2016) Deictic tools can limit the emergence of referential symbol systems. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Emilia Garcia-Casademont

Garcia-Casademont, E. (2017). A Case Study in the Emergence of Recursive Phrase Structure. In First Complex Systems Digital Campus World E-Conference 2015 (pp. 333-336). Springer, Cham.

Emily Morgan

(2016) Frequency-dependent regularization in iterated learning. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Erica Cartmill

Cartmill, E. A., Hunsicker, D., & Goldin-Meadow, S. (2014). Pointing and naming are not redundant: Children use gesture to modify nouns before they modify nouns in speech. Developmental psychology, 50(6), 1660.

Esther Clarke

Clarke, E., Reichard, U. H., & Zuberbühler, K. (2015). Context-specific close-range “hoo” calls in wild gibbons (Hylobates lar). BMC evolutionary biology, 15(1), 56.

Eva Zehentner

(2016) A game theoretic account of semantic subjectification in the cultural evolution of languages. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Evelina Fedorenko

Piantadosi, S. T., & Fedorenko, E. (2016). Infinitely productive language can arise from chance under communicative pressure.

Federica Cavicchio

Cavicchio (2016) Are emotional displays an evolutionary precursor to compositionality in language?. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Fiona Jordan

Jordan, FM & Huber, B, 2013, ‘Evolutionary approaches to cross-cultural anthropology’. Cross-Cultural Research, vol 47., pp. 91-101

Florencia Reali

Reali, F., Chater, N., & Christiansen, M. H. (2014, March). The paradox of linguistic complexity and community size. In Proceedings of the 10th International Conference on the Evolution of Language (EVOLANG X). Singapore: World Scientific Publishing Co. Pte. Ltd (pp. 270-279).

Francesca Tria

Tria (2016) Modeling the emergence of creole languages. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Gabriella Vigliocco

Vigliocco, G., Perniss, P., & Vinson, D. (2014). Language as a multimodal phenomenon: implications for language learning, processing and evolution.

Hannah Cornish

Cornish, H., Dale, R., Kirby, S., & Christiansen, M. H. (2017). Sequence Memory Constraints Give Rise to Language-Like Structure through Iterated Learning. PloS one, 12(1), e0168532.

Hannah Haynie

Haynie, H., Bowern, C., & LaPalombara, H. (2014). Sound symbolism in the languages of Australia. PloS one, 9(4), e92852.

Hannah Little

(2016) Emergence of signal structure: effects of duration constraints. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Heidi Lyn

Lyn, H. (2017). The question of capacity: Why enculturated and trained animals have much to tell us about the evolution of language. Psychonomic Bulletin & Review, 24(1), 85-90.

Hope Morgan

(2016) The effect of modality on signal space in natural languages. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Irene Pepperberg

Pepperberg, I. M. (2016). Animal language studies: What happened? Psychonomic Bulletin & Review Psychon Bull Rev. doi:10.3758/s13423-016-1101-y

Irit Meir

Meir, I., Aronoff, M., Börstell, C., Hwang, S. O., Ilkbasaran, D., Kastner, I., … & Sandler, W. (2017). The effect of being human and the basis of grammatical word order: Insights from novel communication systems and young sign languages. Cognition, 158, 189-207.

Janet Mann

Mann, J., & Singh, L. (2015). Culture, Diffusion, and Networks in Social Animals. Emerging Trends in the Social and Behavioral Sciences: An Interdisciplinary, Searchable, and Linkable Resource.

Jasmeen Kanwal

(2016) The evolution of Zipf’s law of abbreviation. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Jennifer Culbertson

Culbertson, J., & Newport, E. L. (2015). Harmonic biases in child learners: In support of language universals. Cognition, 139, 71-82.

Jesse Snedeker

Kocab, A., Senghas, A., & Snedeker, J. (2016). The emergence of temporal language in Nicaraguan Sign Language. Cognition, 156, 147-163.

Jiani Chen

Chen, J., & ten Cate, C. (2015). Zebra finches can use positional and transitional cues to distinguish vocal element strings. Behavioural processes, 117, 29-34.

Joan Bybee

Bybee, Joan. Language change. Cambridge University Press, 2015.

Joanna Bryson

Bryson, J.J. (2007). Embodiment vs. Memetics. Mind & Society, 7(1):77-94. [Link]

Kate Arnold

Arnold, K & Zuberbuehler, K 2013, ‘Female putty-nosed monkeys use experimentally altered contextual information to disambiguate the cause of male alarm calls’ PLoS One, vol 8, no. 6, e65660. DOI: 10.1371/journal.pone.0065660

Kathleen Dudzinski

Dudzinski, K., & Frohoff, T. (2014). Dolphin mysteries: Unlocking the secrets of communication. Yale University Press.

Katie Collier

(2016) Dwarf mongooses combine meaningful alarm calls. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Katie Slocombe

Fedurek, P., & Slocombe, K. E. (2011). Primate vocal communication: a useful tool for understanding human speech and language evolution?. Human Biology, 83(2), 153-173.

Kim Bard

Bard, K. A. (2016). Dyadic interactions, attachment and the presence of triadic interactions in chimpanzees and humans. Infant Behavior and Development.

Kirsty Graham

(2016) Intentional meaning of bonobo gestures. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Lilia Rissman

Rissman (2016) Strategies in gesture and sign for demoting an agent: effects of language community and input . The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Ljiljana Progovac

Progovac, L. (2016) A gradualist scenario for language evolution: Precise linguistic reconstruction of early human (and Neandertal) grammars. Frontiers in Psychology 2016

Limor Raviv

Raviv, L., & Arnon, I. (2016). Language evolution in the lab: The case of child learners. In A. Papagrafou, D. Grodner, D. Mirman, & J. Trueswell (Eds.), Proceedings of the 38th Annual Meeting of the Cognitive Science Society (CogSci 2016). Austin, TX: Cognitive Science Society (pp. 1643-1648). Austin, TX: Cognitive Science Society.

Lynn Perry

Perry (2016) Early learned words are more iconic. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Madza Farias-Virgens

(2016) Evolution of convergent transcriptional specializations in the brains of humans and song-learning birds. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Maggie Tallerman

Tallerman M. Can the integration hypothesis account for language evolution?. Journal of Neurolinguistics 2016, (ePub ahead of Print).

Marie Montant

Montant (2016) Make new with old: human language in phylogenetically ancient brain regions. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Marieke Schouwstra

Schouwstra, M. (2016). Temporal Structure in Emerging Language: From Natural Data to Silent Gesture. Cognitive Science.

Marieke Woensdregt

(2016) The cultural co-evolution of language and mindreading. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Marlen Fröhlich

Fröhlich, M.; Müller, G.; Zeiträg, C.; Wittig, R. M.; Pika, S.: Gestural development of chimpanzees in the wild: the impact of interactional experience. Animal Behaviour (2017)

Megan Broadway

(2016) Signature whistles in an introduction context. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Michelle Spierings

(2016) Rule learning in birds: zebra finches generalize by positional similarities, budgerigars by the structural rules.. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Molly Flaherty

Flaherty (2016) Do lab attested biases predict the structure of a new natural language? The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Molly Lewis

Lewis, M. & Frank, M. C. (2016). The length of words reflects their conceptual complexity. Cognition. 153, 182-195.

Monica Tamariz

Tamariz, M., & Kirby, S. (2016). The cultural evolution of language. Current Opinion in Psychology, 8, 37-43.

Monika Pleyer

Pleyer, M. & Pleyer, M. (2016). The Evolution of Im/politeness. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Mutsumi Imai

Imai, M., Kanero, J., & Masuda, T.(2016). The Relation between Language, Culture and Thought. Current Opinion in Psychology, 8, 70–77.

Natalie Sebanz

Milward, S. J., & Sebanz, N. (2016). Mechanisms and development of self–other distinction in dyads and groups. Phil. Trans. R. Soc. B, 371(1686), 20150076.

Nicky Clayton

Clayton, N. S. (2015). Ways of thinking: from crows to children and back again. The Quarterly Journal of Experimental Psychology, 68(2), 209-241.

Oksana Tkachman

(2016) Arbitrariness of iconicity: the sources (and forces) of (dis)similarities in iconic representations . The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Olga Feher

Fehér, O., Ljubicic, I., Suzuki, K., Okanoya, K. & Tchernichovski, O. (2017). Statistical learning in songbirds: from self-tutoring to song culture. Philosophical Transactions of the Royal Society B. doi: 10.1098/rstb.2016.0053.

Olga Vasileva

(2016) Language evolution in ontogeny and phylogeny. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Pamela Perniss

Perniss, P., & Vigliocco, G. (2014). The bridge of iconicity: from a world of experience to the experience of language. Phil. Trans. R. Soc. B, 369(1651), 20130300.

Piera Filippi

Filippi (2016) Humans recognize vocal expressions of emotional states universally across species. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Rebecca Grollemund

Grollemund, R., Branford, B., Bostoen, K., Meade, A., Venditti, C. & Pagel, M. (2015). Bantu expansion shows habitat alters the route and pace of human dispersals. Proceedings of the National Academy of Sciences (PNAS), 112:43, pp. 13296-13301. [link]

Rie Asano

(2016) On a music-ready brain: neural basis, mechanisms, and their contribution to the language evolution. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Rose Stamp

Stamp (2016) The grammar of the body and the emergence of complexity in sign languages. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Ruth Sonnweber

Sonnweber, R., Ravignani, A., & Fitch, W. T. (2015). Non-adjacent visual dependency learning in chimpanzees. Animal cognition, 18(3), 733-745.

Sabine van der Ham

(2016) Catergory learning in audition, touch, and vision. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Sabrina Engesser

(2016) Meaningful call combinations and compositional processing in a social bird. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Sarah Hrdy

Hrdy, S. B. (2016). Development plus social selection in the emergence of “emotionally modern” humans. Childhood: Origins, Evolution, and Implications, 11.

Sharon Thompson-Schill

Fedorenko, E., & Thompson-Schill, S. L. (2014). Reworking the language network. Trends in cognitive sciences, 18(3), 120-126.

Shiri Lev-Ari

Lev-Ari, S., & Peperkamp, S. (2017). Language for $200: Success in the environment influences grammatical alignment. Journal of Language Evolution. Advance online publication. doi:10.1093/jole/lzw012

Simone Pika

Fröhlich, M.; Müller, G.; Zeiträg, C.; Wittig, R. M.; Pika, S.: Gestural development of chimpanzees in the wild: the impact of interactional experience. Animal Behaviour (2017)

Sonia Harmand

Lewis, Jason E., and Sonia Harmand. “An earlier origin for stone tool making: implications for cognitive evolution and the transition to Homo.” Phil. Trans. R. Soc. B 371.1698 (2016): 20150233.

Sonja Vernes

Vernes, S. C. (2016). What bats have to say about speech and language. Psychonomic Bulletin & Review. Advance online publication. doi:10.3758/s13423-016-1060-3

Susan Goldin-Meadow

Goldin-Meadow, S., & Yang, C. (2016). Statistical evidence that a child can create a combinatorial linguistic system without external linguistic input: Implications for language evolution. Neuroscience & Biobehavioral Reviews.

Tessa Verhoef

Verhoef (2016) Iconicity, naturalness and systematicity in the emergence of sign language structure. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Vanessa Ferdinand

Ferdinand (2016) Word learners regularize synonyms and homonyms similarly. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Vera Kempe

Kempe, V., Gauvrit, N., & Forsyth, D. (2015). Structure emerges faster during cultural transmission in children than in adults. Cognition, 136, 247-254.

Wendy Sandler

Sandler, Wendy (to appear). What Comes First in Language Emergence? In N. Enfield (Ed.). Dependencies in Language: On the Casual Ontology of Linguistic Systems. Language Science Press, Studies in Diversity Linguistics Series.

Yasamin Motamedi

(2016) Linguistic structure emerges in the cultural evolution of artificial sign languages. The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

Zanna Clay

Clay (2016) Functionally flexible vocalizations in wild bonobos (pan pansicus). The Evolution of Language: Proceedings of the 11th International Conference (EVOLANG11)

 

 

10 post-docs join new language evolution group in Nijmegen

In 2016 and 2017, ten post-doc researchers will join the MPI for Psycholinguistics in Nijmegen to form the Language Evolution and Interaction Scholars of Nijmegen group (LEvInSON).

The group will explore the biological and cultural origins of language, and how they are linked through social interaction. The group, led by Stephen Levinson, Seán Roberts and Mark Dingemanse, will be hosted by the Language and Cognition department.

The visitors include researchers specializing in experimental approaches (Hannah Little, Yasamin Motamedi, Alan Nielsen, Justin Sulik), computational modelling (Kevin Stadler, Bill Thompson), animal communication (Marcus Perlman, Andrea Ravignani), comparative linguistics (Piera Filipi), and conversational interaction (Ashley Micklos).

levinsongroup

Tessa Verhoef, who was awarded a VENI grant to study the evolution of linguistic structure, will also join the group.  All together, this will be one of the largest groups studying language evolution in the world.

Several senior researchers will visit throughout the period, including Vera Kempe (Abertay University), Monica Tamariz (University of Edinburgh), Gary Lupyan (University of Wisconsin-Madison), Cedric Boeckx (ICREA/Universitat de Barcelona) and Bart de Boer (Vrije Universiteit Brussel).

Double-blind reviewing at EvoLang 11 reveals gender bias

In a new paper in the Journal of Language Evolution, Tessa Verhoef and I analyse reviewer ratings for papers submitted to the EvoLang conference between 2012 and 2016 .  In the most recent conference, we trialed double-blind review for the first time, and we wanted to see if hiding the identity of authors revealed any biases in reviewers’ ratings.

We found that:

  • Proportionately few papers are submitted from female first authors.
  • In single-blind review, there was no big difference in average ratings for papers by male or female first authors …
  • … but female first-authored papers were rated significantly higher than male first authored papers in the double-blind condition.

There are many possible explanations of these findings, but they are indicative of a bias against female authors.  This fits with a wider literature of gender biases in science.  We suggest that double-blind review is one tool that can help reduce the effects of gender biases, but does not tackle the underlying problem directly.  We were pleased to see better representation of women on the most recent EvoLang talks and plenary speaker list, and look forward to making our field more inclusive.

The paper is available, free and open-access, at the Journal of Language Evolution.  The data and statistical code is also available on github.