This dissertation concerns the computational modelling of early life development of music perception and cognition. Experimental psychology and neuroscience show results that suggest that the development of musical representations in infancy, whether concerning pitch or rhythm features, depend on exposure both to music and language. Early musical and linguistic skills seem to be, therefore, tangled in ways we are yet to characterize. In parallel, computational modelling has produced powerful frameworks for the study of learning and development. The use of these models for studying the development of music information perception and cognition, connecting music and language still remains to be explored.
This way, we propose to produce computational solutions suitable for studying factors that contribute to shape our cognitive structure, building our predispositions that allow us to enjoy and make sense of music. We will also adopt a comparative approach to the study of early development of musical predispositions that involves both music and language, searching for possible interactions and correlations. With this purpose, we first address pitch representation (absolute vs relative) and its relations with development. Simulations have allowed us to observe a parallel between learning and the type of pitch information being used, where the type of encoding that was being used influenced the ability of the model to perform a discrimination task correctly. Next, we have performed a prosodic characterization of infant-directed speech and singing by comparing rhythmic and melodic patterning in two Portuguese (European and Brazilian) variants. In the computational experiments, rhythm related descriptors exhibited a strong predictive ability for both speech and singing language variants’ discrimination tasks, presenting different rhythmic patterning for each variant. This reveals that the prosody of the surrounding sonic environment of an infant is a source of rich information and rhythm as a key element for characterizing the prosody from language and songs from each culture. Finally, we propose a computational model based on temporal information processing and representation for exploring how the temporal prosodic patterns of a specific culture influence the development of rhythmic representations and predispositions. The simulations show that exposure to the surrounding sound environment influences the development of temporal representations and that the structure of the exposure environment, specifically the lack of maternal songs, has an impact on how the model organizes its internal representations.
We conclude that there is a reciprocal influence between music and language. It is from the exposure to the structure of the sonic background that we shape our cognitive structure, which supports our understanding of musical experience. Among the sonic background, language’s structure has a predominant role in the building of musical predispositions and representations.
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