Language Evolution and Computation Bibliography

Human language shows combinatoriality in its phonology (both in speech and in sign language) and its grammar, while both types appear to be absent in the communication systems of our closest evolutionary relatives. In this article, we observe that productive combinatoriality is difficult to evolve, because it requires multiple components to be put in place simultaneously for it to function. To understand how it nevertheless evolved in human language, we focus on combinatoriality in phonology, for which most evidence is available. We discuss findings and theories from three domains: linguistics (descriptive, experimental and corpus linguistics), comparative biology (including some fossil indicators) and (computer) models. We tentatively conclude that many of the biological prerequisites for combinatorial phonology and compositional semantics are shared with other animals, but that a uniquely human pressure for large vocabularies and uniquely human processes of cultural evolution are key in understanding the origins of combinatoriality in language

Two computer simulations are investigated that model interaction of cultural evolution of language and biological evolution of adaptations to language. Both are agent-based models in which a population of agents imitates each other using realistic vowels. The agents evolve under selective pressure for good imitation. In one model, the evolution of the vocal tract is modeled; in the other, a cognitive mechanism for perceiving speech accurately is modeled. In both cases, biological adaptations to using and learning speech evolve, even though the system of speech sounds itself changes at a more rapid time scale than biological evolution. However, the fact that the available acoustic space is used maximally (a self-organized result of cultural evolution) is constant, and therefore biological evolution does have a stable target. This work shows that when cultural and biological traits are continuous, their co-evolution may lead to cognitive adaptations that are strong enough to detect empirically.

Interest in the origins and evolution of language has been around for as long as language has been around. However, only recently has the empirical study of language come of age. We argue that the field has sufficiently advanced that it now needs its own journal—the Journal of Language Evolution.

In language, recombination of a discrete set of meaningless building blocks forms an unlimited set of possible utterances. How such combinatorial structure emerged in the evolution of human language is increasingly being studied. It has been shown that it can emerge when languages culturally evolve and adapt to human cognitive biases. How the emergence of combinatorial structure interacts with the existence of holistic iconic form‐meaning mappings in a language is still unknown. The experiment presented in this paper studies the role of iconicity and human cognitive learning biases in the emergence of combinatorial structure in artificial whistled languages. Participants learned and reproduced whistled words for novel objects with the use of a slide whistle. Their reproductions were used as input for the next participant, to create transmission chains and simulate cultural transmission. Two conditions were studied: one in which the persistence of iconic form‐meaning mappings was possible and one in which this was experimentally made impossible. In both conditions, cultural transmission caused the whistled languages to become more learnable and more structured, but this process was slightly delayed in the first condition. Our findings help to gain insight into when and how words may lose their iconic origins when they become part of an organized linguistic system.

This paper reviews how the structure of form and meaning spaces influences the nature and the dynamics of the form-meaning mappings in language. In general, in a structured form or meaning space, not all forms and meanings are equivalent: some forms and some meanings are more easily confused with each other than with other forms or meanings. We first give a formalization of this idea, and explore how it influences robust form-meaning mappings. It is shown that some fundamental properties of human language, such as discreteness and combinatorial structure as well as universals of sound systems of human languages follow from optimal communication in structured form and meaning spaces. We also argue that some properties of human language follow less from these fundamental issues, and more from cognitive constraints.

We then show that it is possible to experimentally investigate the relative contribution of functional constraints and of cognitive constraints. We illustrate this with an example of one of our own experiments, in which experimental participants have to learn a set of complex form-meaning mappings that have been produced by a previous generation of participants. Theoretically predicted properties appear in the sets of signals that emerge in this iterated learning experiment.

This article provides an overview on infant-directed speech and language evolution. Infant-directed speech is defined as a set of speech registers that caretakers use to address infants. There are at least three different kinds of infant-directed speech, first, which is used to get the infant's attention, second, which is used to soothe the infant, and last, which is used to address the infant with linguistically meaningful utterances. All kinds of infant- directed speech are characterized by slower speech rate and larger intonation contours. Attention-getting infant-directed speech is characterized by higher volume and extreme intonation excursions, but it does not necessarily consist of meaningful utterances. Soothing infant-directed speech is characterized by lower volume, sometimes even whispered speech, and very flowing intonation contours. Caretakers use infant-directed speech automatically when addressing infants, even without being aware of doing it. They also automatically adapt the complexity of their speech to the level of linguistic competence of the infant. The infant-directed speech also appears to be nearly universal cross-culturally and a similar register is attested in signed languages. Computational experiments have revealed that it is easier to acquire vowel categories on the basis of infant-directed speech than on the basis of adult-directed speech. Other computational experiments have shown that infant-directed speech can help to preserve stability of vowel systems over time.

This article focuses on the two different levels that are used to define language. One of the levels is the individual level, where detailed individual behavior is studied and the other is the population level, where individual behavior is averaged and abstracted, and more general trends and processes are studied. Both these levels are intertwined and interdependent and such interaction between the levels can lead to a phenomenon called self- organization. Self-organization is the spontaneous emergence of order in a system that must be spontaneous. The interaction between self-organization and biological evolution is fundamental to understanding the evolution of language. Biological evolution determines the dynamics and the boundary conditions of the self-organizing process. Self-organization causes the language to converge on a limited number of states, the properties of which then determine the fitness of the language-using agents. Biological evolution then selects adaptations that help cope with the properties of the states resulting from self-organization. There are two perspectives on self-organization in language. First is the perspective of an individual's linguistic knowledge, in which linguistic items such as words or speech sounds can be considered as the microscopic level and the complete linguistic system can be considered as the macroscopic level. The second perspective is that of language in a population of speakers, where individual language users constitute the microscopic level, and the whole language community constitutes the macroscopic level.

Abstract A fundamental characteristic of human speech is that it uses a limited set of basic building blocks (phonemes, syllables), that are put to use in many different combinations to mark differences in meaning. This article investigates the evolution of such combinatorial ...

Human speech has been investigated with computer models since the invention of digital computers, and models of the evolution of speech first appeared in the late 1960s and early 1970s. Speech science and computer models have a long shared history because speech is a physical signal and can be modeled accurately. This article gives a brief overview of the use of computer models in the study of the evolution of the vocal tract. We also present a critical case study of one model that has been used to study the vocal abilities of Neanderthals. We argue that this study contains subtle but fatal flaws which invalidate the conclusions drawn from the model, illustrating the dangers of applying computer models outside the area for which they have been developed. Future models need to make use of a broader database of anatomical and physiological data from other animals, especially nonhuman primates, to understand the path leading to modern Homo sapiens.

This methodological article serves as an introduction to this special issue, whose aim is to encourage more and better interaction between empirical studies and computer modeling with regard to the study of language evolution. We argue that research into the field of language evolution is so complex that computer modeling forms an essential tool to generate predictions based on some, possibly descriptive, theory in order to falsify that theory. Falsification should be carried out by comparing the generated predictions with empirical data. In order to improve the quality of the predictions and thus the reliability of the falsification process, we stress the importance of initializing the computer model with empirical data. The papers in this special issue provide some concrete examples and new proposals of applying the suggested methodology.

In order to make distinctive speech sounds, it is necessary to control two separate acoustic cavities. There has been a longstanding debate about whether a lowered larynx is essential for this. Lieberman and Crelin have used it as an argument against speech in Neanderthals. This claim is controversial, not only for paleontological reasons, but also because researchers do not agree on the need of a lowered larynx for distinctive speech. Researchers using similar methods (computer modeling) arrive at opposite conclusions. The problem is that one needs to take articulatory and anatomical constraints into account when investigating the acoustic implications of vocal tract morphology.

In order to study what the effect of lowering the larynx is, a reimplementation of Mermelstein s vocal tract model has been made. This is a computer model of the geometry of the (human male) vocal tract, whose controls correspond to the actions of the muscles involved in speech. This model was used to explore the possible articulations and the corresponding acoustic signals of different vocal tract geometries.

Experiments were run with the original male model, a model of the female vocal tract and a model that is a combination of these two tracts. It was also found that the female vocal tract is better than the male one. This observation was confirmed by a reanalysis of the data from the Peterson and Barney study. This establishes an evolutionary advantage of a vocal tract that has a pharyngeal and oral cavity of equal length (as in the female tract). It has a larger signaling space than the male tract. Males probably had evolutionary advantage from size exaggeration, as proposed by Fitch. It must be noted however, that the differences found so far are significant but small.

A fundamental, universal property of human language is that its phonology is combinatorial. That is, one can identify a set of basic, distinct units (phonemes, syllables) that can be productively combined in many different ways. In this paper, we develop a methodological framework based on evolutionary game theory for studying the evolutionary transition from holistic to combinatorial signal systems, and use it to evaluate a number of existing models and theories. We find that in all problematic linguistic assumptions are made or crucial components of evolutionary explanations are omitted. We present a novel model to investigate the hypothesis that combinatorial phonology results from optimizing signal systems for perceptual distinctiveness. Our model differs from previous models in three important respects. First, signals are modeled as trajectories through acoustic space; hence, both holistic and combinatorial signals have a temporal structure. Second, acoustic distinctiveness is defined in terms of the probability of confusion. Third, we show a path of ever increasing fitness from unstructured, holistic signals to structured signals that can be analyzed as combinatorial. On this path, every innovation represents an advantage even if no-one else in a population has yet obtained it.

This paper describes the uses of computer models in studying the evolution of language. Language is a complex dynamic system that can be studied at the level of the individual and at the level of the population. Much of the dynamics of language evolution and language change occur because of the interaction of these two levels. It is argued that this interaction is too complicated to study with pen-and-paper analysis alone and that computer models therefore provide a useful tool for understanding language evolution. Different techniques are presented: direct optimization, genetic algorithms and agent-based models. Of each of these techniques, an example is briefly presented. Also, the importance of correctly measuring and presenting the results of computer simulations is stressed.

This paper investigates the interaction between cultural evolution and biological evolution in the emergence of phonemic coding in speech. It is observed that our nearest relatives, the primates, use holistic utterances, whereas humans use phonemic utterances. It can therefore be argued that our last common ancestor used holistic utterances and that these must have evolved into phonemic utterances. This involves co-evolution between a repertoire of speech sounds and adaptations to using phonemic speech. The culturally transmitted system of speech sounds influences the fitness of the agents and could conceivably block the transition from holistic to phonemic speech. This paper investigates this transition using a computer model in which agents that can either use holistic or phonemic utterances co-evolve with a lexicon of words. The lexicon is adapted by the speakers to conform to their preferences. It is shown that although the dynamics of the transition are changed, the population still ends up of agents that use phonemic speech.

Much is known about the evolution of speech. Fossil evidence points to modern adaptations for speech appearing between 1.5 million and 500,000 years ago. Studies of vocal behavior in apes show the ability to use combinatorial vocalizations in some species (but not chimpanzees) and some cultural influence on vocalizations, but little ability for vocal imitation. For modern speech, the comparison of many languages shows that speech can become extremely complex, but that it can also be astonishingly simple. Finally, the way in which infants acquire speech is becoming increasingly clear. We therefore know about the starting point of the evolution of speech, its end point and some steps in between.

Much less is known about the exact scenario and the dynamics of the evolution of the acquisition of speech. As it involves co-evolution between culturally transmitted sounds and genetic evolution, the dynamics are complex. Computer models are therefore ideal for studying these dynamics. This paper presents a computer model of the co-evolution between a repertoire of speech sounds and a population of learners that can either represent a lexicon holistically or combinatorially. It shows that cultural influences can change the dynamics of the transition between a population of holistic and combinatorial learners.

In this paper we present our work on developing a shared repertoire of action categories through imitation. A population of robotic agents invents and shares a repertoire of actions by engaging in imitative interactions. We present an experimental set-up which enables us to investigate what properties agents should have in order to achieve this. Among these properties are: being able to determine the other's actions from visual observation and doing incremental unsupervised categorisation of actions.

This book addresses universal tendencies of human vowel systems from the point of view of self-organization. It uses computer simulations to show that the same universal tendencies found in human languages can be reproduced in a population of artificial agents. These agents learn and use vowels with human-like perception and production, using a learning algorithm that is cognitively plausible. The implications of these results for the evolution of language are then explored.

This paper describes a model of the emergence and the universal structural tendencies of vowel systems. Both are considered as the result of self-organisation in a population of language users. The language users try to imitate each other and to learn each other's vowel systems as well as possible under constraints of production and perception, while at the same time maximising the number of available speech sounds. It is shown through computer simulations that coherent and natural sound systems can indeed emerge in populations of artificial agents. It is also shown that the mechanism that is responsible for the emergence of sound systems can be used for learning existing sound systems as well. Finally, it is argued that the simulation of agents that can only produce isolated vowels is not enough. More complex utterances are needed for other interesting universals of sound systems and for explaining realistic sound change.

This paper presents a computer simulation of the emergence of vowel systems in a population of agents. The agents (small computer programs that operate autonomously) are equipped with a realistic articulatory synthesizer, a model of human perception and the ability to imitate and learn sounds they hear. It is shown that due to the interactions between the agents and due to self-organization, realistic vowel repertoires emerge. This happens under a large number of different parameter settings and therefore seems to be a very robust phenomenon. The emerged vowel systems show remarkable similarities with the vowel systems found in human languages. It is argued that self-organization probably plays an important role in determining the vowel inventories of human languages and that innate predispositions are probably not necessary to explain the universal tendencies of human vowel systems.

This paper describes computer simulations that investigate the role of self-organisation in explaining the universals of human vowel systems. It has been observed that human vowel systems show remarkable regularities, and that these regularities optimise acoustic distinctiveness and are therefore adaptive for good communication. Traditionally, universals have been explained as the result of innate properties of the human language faculty, and therefore need an evolutionary explanation. In this paper it is argued that the regularities emerge as the result of self-organisation in a population and therefore need not be the result of biological evolution. \\ The hypothesis is investigated with two different computer simulations that are based on a population of agents that try to imitate each other as well as possible. Each agent can produce and perceive vowels in a human-like way and stores vowels as articulatory and acoustic prototypes. The aim of the agents is to imitate each other as well as possible. \\ It will be shown that successful repertoires of vowels emerge that show the same regularities as human vowel systems.

The research described in this thesis tries to explain the origins and the struc- ture of human sound systems (and more specifically human vowel systems) as the result of self-organisation in a population under functional con- straints. These constraints are: acoustic distinctiveness, articulatory ease and ease of learning. The process is modelled with computer simulations, following the meth- odology of artificial life and artificial intelligence. The research is part of a larger re- search effort into understanding the origins and the nature of language and intelli- gence.

The emergence of sound systems is studied in a setting called the imitation game. In an imitation game, agents from a population interact in order to imitate each other as well as possible. Imitation is a binary process: it is either successful or a failure. Agents are able to produce and perceive speech sounds in a human-like way, and to adapt and extend their repertoires of speech sounds in reaction to the outcome of the imitation games. The agents' vowel repertoires are initially empty and are bootstrapped by random insertion of a speech sound when an agent with an empty repertoire wants to produce a sound. When the agents' repertoires are not empty anymore, random insertion does not happen anymore, except with very low probability. This low-probability random insertion is done in order to keep a pres- sure on the agents to extend their number of vowels. .

As the agents' repertoires are initially empty and their production and percep- tion are not biased towards any language in particular, the systems of speech sounds that emerge are language-independent and can be considered predictions of the kinds of systems of speech sounds that can be found in human languages.

The main focus of the thesis is on the emergence of vowel systems. It is shown that coherent, successful and realistic vowel systems emerge for a wide range of pa- rameter settings in the simulation. When the vowel systems are compared with the types of vowel systems that are found in human languages, remarkable similarities are found. Not only are the most frequently found human vowel systems predicted, (this could already be done with direct optimisation of acoustic distinctiveness) but also less frequently occurring vowel systems are predicted in approximately the right proportions.

Variations on the basic imitation game show that it is remarkably robust. Not only do coherent, successful and realistic vowel systems emerge for a large number of parameter settings, but they also emerge when either the imitation game or the agents are changed qualitatively. Coherent and realistic systems still emerge when the perception and production of the agents are changed. Even if the rules of the imitation game are slightly changed, coherent and realistic systems still emerge. Of course, there are circumstances under which no systems emerge, indicating that the process is non-trivial.

It is also shown that the vowel systems can emerge and be preserved in chang- ing populations. When old agents are removed from the population, and new, empty agents are added, coherent and realistic vowel systems can still emerge, provided that the replacement rate is not too high. It is also shown in the thesis that vowel systems can be preserved in a population, even though all original agents in it have been replaced. Furthermore, it is shown that under certain circumstances it can be advantegeous to have an age-structure in the population, so that older agents learn less quickly than young ones.

Finally, some experiments with more complex utterances are presented in the thesis. An experiment with artificial CV-syllables is presented and it is shown that, although phonemically coded (as opposed to holistically coded) systems can emerge, this simulation is much harder and much more sensitive to parameter changes than the vowel simulation. This probably has to do with the fact that in the case of CV- syllables multiple independent and partly contradictory constraints have to be satis- fied simultaneously, whereas in the vowel simulations, only one constraint (acoustic distinctiveness) is really important. Also, the first attempts at building a system that can produce complex and dynamic utterances without any constraints on their structure are presented, and it is argued that the main obstacle to getting such a system to work is the mapping from acoustic signals back to articulatory com- mands.

The conclusion of the thesis is that universal tendencies of human vowel sys- tems, and probably of human sound systems in general can be explained as the re- sult of self-organisation in a population of agents that try to communicate as well as possible under articulatory and acoustic constraints. The articulatory and acoustic constraints cause the emerging sound systems to tend towards articulatory and acoustic optimality. However, the fact that the agents communicate in a population forces them to conform to the sound system in the population and causes sub- optimal systems to emerge as well.