The paper surveys work on the computational modeling of the origins and evolution of language. The main approaches are clarified and some example experiments from the domains of the evolution of communication, phonetics, lexicon formation, and syntax are discussed. 1 Introduction The paper surveys research in which software simulations and experiments with robotic agents are used to explore the viewpoint that language is a complex dynamical system. The main goal of the paper is to outline the approaches and show example experiments. Much more work needs to be done to arrive at a full-fledged theory of the origins of language and even about the work already done much more can be said than is possible in a single paper. Nevertheless, I hope to show that a new exciting approach to the study of the origins and evolution of language is taking shape. The rest of the paper is in four parts. The next section clarifies the notion of a complex system and the multi-agent perspective. Section 3...

The speech code is a vehicle of language: it defines a set of forms used by a community to carry information. Such a code is necessary to support the linguistic interactions that allow humans to communicate. How then may a speech code be formed prior to the existence of linguistic interactions? Moreover, the human speech code is discrete and compositional, shared by all the individuals of a community but different across communities, and phoneme inventories are characterized by statistical regularities. How can a speech code with these properties form? We try to approach these questions in the paper, using the ‘‘methodology of the artificial’’. We build a society of artificial agents, and detail a mechanism that shows the formation of a discrete speech code without presupposing the existence of linguistic capacities or of coordinated interactions. The mechanism is based on a low-level model of sensory–motor interactions. We show that the integration of certain very simple and non-language-specific neural devices leads to the formation of a speech code that has properties similar to the human speech code. This result relies on the self-organizing properties of a generic coupling between perception and production within agents, and on the interactions between agents. The artificial system helps us to develop better intuitions on how speech might have appeared, by showing how self-organization might have helped natural selection to find speech.

Chomsky and Halle (1968) and many formal linguists rely on the notion of a universally available phonetic space defined in discrete time. This assumption plays a central role in phonological theory. Discreteness at the phonetic level guarantees the discreteness of all other levels of language. But decades of phonetics research demonstrate that there exists no universal inventory of phonetic objects. We discuss three kinds of evidence: first, phonologies differ incommensurably. Second, some phonetic characteristics of languages depend on intrinsically temporal patterns, and, third, some linguistic sound categories within a language are different from each other despite a high degree of overlap that precludes distinctness. Linguistics has mistakenly presumed that speech can always be spelled with letter-like tokens. A variety of implications of these conclusions for research in phonology are discussed.* The generative paradigm of language description (Chomsky 1964, 1965, Chomsky & Halle 1968) has dominated linguistic thinking in the United States for many years. Its specific claims about the phonetic basis of linguistic analysis still provide the cornerstone of most linguistic research. Many criticisms have been raised against the phonetic claims of the Sound pattern of English (Chomsky & Halle 1968), some from early on

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To what extent can Optimality Theory (Prince and Smolensky 1993/2004) provide theoretical phonology a satisfactory formalization of markedness theory? This is a central question for linking OT and actual empirical patterns: � of Figure 6 in Chapter 2’s Integrated Connectionist/Symbolic Cognitive Architecture (ICS) map. Through several case studies, it is argued here that OT makes possible formal markedness-based explanations of both broad universal generalizations and complex language-particular patterns—provided the theory incorporates conjunctive constraint interaction. The nonderivational character of OT drives the development of a nonstandard type of constituent in phonological representations: the headed feature domain. The empirical realms investigated are

The goal of this paper is to examine the relationship between vowel height and nasalization, a relationship that argues rather directly for the importance to phonological patterning of the perceptual distinctiveness of contrast. It thus adds to the list of cases making this point (see Flemming 1995, and also N Chiosin and Padgett 1997 for others), and strengthens the case for an output-oriented conception of contrast: in order for the perceptual distinctiveness of a contrast to be evaluated at the surface, contrast itself must be discernable by constraints at the surface

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We propose and describe several methods for using speech power as an estimate of intentional loudness, and a mapping from this loudness estimate to a continuous control. This is performed in the context of a novel voice-based human-computer interface designed to enable individuals with motor impairments to use vocal tract parameters for both discrete and continuous control tasks. The interface uses vocal gestures to control continuous movement and discrete sounds for other events. We conduct a user preference survey to gauge user reaction to the various methods in a mouse cursor control context. We find that loudness is an effective mechanism to control mouse cursor movement speed when mapping vocalic gestures to spatial position. 1.

this paper tries to explain the emergence and structure of systems of speech sounds. It investigates how a coherent system of speech sounds can emerge in a popu- lation of agents and how the constraints under which the system emerges impose structure through self-organisation. If self-organisation can explain structure, then innate and biologi- cally evolved mechanisms are not necessary. This effectively decreases the number of linguistic phenomena that have to be explained by biological evolution

Vocal Joystick is a mechanism that enables individuals with motor impairments to make use of vocal parameters to control objects on a computer screen (buttons, sliders, etc.) and ultimately will be used to control electro-mechanical instruments (e.g., robotic arms, wireless home automation devices). In an effort to train the VJ-system, speech data from the TIMIT speech corpus was initially used. However, due to problematic issues with co-articulation, we began a large data collection effort in a controlled environment that would not only address the problematic issues, but also yield a new vowel corpus that was representative of the utterances a user of the VJ-system would use. The data collection process evolved over the course of the effort as new parameters were added and as factors relating to the quality of the collected data in terms of the specified parameters were considered. The result of the data collection effort is a vowel corpus of approximately 11 hours of recorded data comprised of approximately 23500 sound files of the monophthongs and vowel combinations (e.g. diphthongs) chosen for the Vocal Joystick project varying along the parameters of duration, intensity and amplitude. This paper discusses how the data collection has evolved since its initiation and provides a brief summary of the resulting corpus. Index Terms: Speech corpora, data collection procedures, speech recognition, Speech HCI for individuals with impairments, Speech/voice-based human-computer interfaces 1.