Thesis (Ph. D.)--University of Oregon, 2002. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 87-99). Also available for download via the World Wide Web; free to University of Oregon users.

Before infants speak their first word, they already produce a large variety of sounds. Whilst the developmental process that leads to speech production is very well documented, little attention is given to how non-linguistic sounds function in the child's everyday environment and whether they show acoustic consistencies similar to those found in the calls of non-human primates. This thesis investigated whether human infants between 11 and 18 months have “calls”. The first study observed 22 infants in their everyday nursery environment in Scotland and identified a number of contexts in which infants produced vocal behaviour. Vocalisations in five of these contexts, giving, declarative pointing, food requests, protests and action requests, were then subjected to an acoustic analysis. Results of the discriminant analysis suggest that four categories of vocal behaviour can be distinguished on the basis of their acoustic properties alone. To investigate whether these calls are part of a universal human repertoire, we conducted a cross-cultural comparison of the acoustic properties of vocal behaviour showed that, despite a slightly higher level of variation; four categories of calls could still be discriminated above chance level. This suggests that human infants possess calls with rather fixed acoustic properties as part of their vocal repertoire in addition to other, more flexible vocal behaviours. In order to assess whether listeners can gain information from these calls, we conducted a playback study with parents, experienced and inexperienced participants. Results show that all participants can categorise all vocalisations above chance level. Parents were the only participants that showed significantly better scores in correctly classifying vocalisations recorded in Scotland over those recorded in Uganda. Overall, the studies demonstrated that infants, as part of their vocal repertoire, produce some classes of calls that have constant acoustic properties across infants from different cultures, and contain information about the infant's activities that can be picked up by a listener.

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Kommunikation entsteht, ohne dass hierfür notwendigerweise semantische oder syntaktische Regeln definiert werden müssen: Irgendwann haben unsere Vorfahren erlernt, miteinander zu kommunizieren, ohne dass ihnen jemand erklärte, wie das geht. In dieser Arbeit wird der philosophischen Frage nachgegangen, wie das möglich ist. Es soll geklärt werden, welche Bedingungen im Abstrakten dafür hinreichend sind, dass Wesen miteinander zu kommunizieren erlernen, und zwar insbesondere, ohne dass man ihnen hierfür eine konkrete Sprache vorgibt. Die Arbeit baut auf neuen Modellen und Erkenntnissen aus der Signalspieltheorie auf. Diese belegen, dass selbst einfache verstärkungsbasierte Lernverfahren in bestimmten Koordinierungsproblemen selbständig erlernen können, Information miteinander auszutauschen. Diese Erkenntnisse werden in dieser Arbeit mit Techniken aus dem maschinellen Lernen, insbesondere aus dem Bereich des deep reinforcement learning, kombiniert. Hiermit soll demonstriert werden, dass rudimentär intelligente Akteure selbstständig in relativ komplexen Sprachen miteinander kommunizieren können, wenn dies einer effizienteren Lösung nicht-trivialer Koordinierungsprobleme dient. Anders als in vergleichbaren Ansätzen, werden die lernfähigen Algorithmen, die in dieser Arbeit zum Einsatz kommen, weder dazu trainiert, real existierende Sprachen zu benutzen, noch werden sie dazu programmiert, künstliche Protokollsprachen zu verwenden. Vielmehr wird ihnen lediglich eine Menge von Signalen vorgegeben. Sowohl die syntaktischen Regeln, wie diese Signale aneinandergereiht werden dürfen, als auch die Semantik der Signale entstehen von alleine. / Communication emerges without the need for explicit definitions of semantic or syntactic rules: At some point, our ancestors learned to communicate with one another without anyone explaining to them how to do that. In this work, I'll try to answer the philosophical question of how that is possible. The goal is to find abstract conditions that are sufficient for the emergence of communication between creatures that do not have any predefined language available to them. This work builds on recent models and insights from the theory of signaling games. There, it is shown that simple reinforcement learning agents are able to learn to exchange meaningful information in suitable coordination problems autonomously. These insights will be combined with more powerful deep reinforcement learning techniques. Thus, it shall be demonstrated that moderately intelligent agents can learn to communicate in relatively complex languages, if this is useful to them in sufficiently non-trivial coordination problems. In contrast to existing work on communication based on artificial intelligence, the learning algorithms that will be applied here, will neither be trained to communicate in an existing natural language, nor will they be hard coded to use a predefined protocol. Instead, they will construct their messages freely from arbitrary sets of signals. The syntactic rules according to which these elementary signals can be chained together, as well as their semantics, will emerge autonomously.