Description
Meaning in spoken languages is communicated via sound. All sound (in spoken languages) is generated by the movements of a small set of speech articulators and their acoustic consequences. How can this physical system, the human vocal tract, communicate such richness of distinctions in meaning? To what extent is the structure of sound patterns in language influenced by constraints of this physical system? This course addresses these questions by seeking to identify ways to better understand the relation between the sound patterns of different languages and their manifestation as physical activity in the vocal tracts of actual speakers. The course begins by providing the necessary concepts and tools for exploring language sound structure. Using software for visualizing dynamic articulatory movements, we study how humans produce consonants and vowels of different languages in isolation and in sequences. We then study how language-specific patterns of consonants and vowels can be described as formal systems of rules and how such patterns can be modeled using tools from mathematics. In the final part, through a sequence of readings and group projects, students tackle issues in the relation between sound patterns and their realization in terms of activity in the vocal tract.
This course emphasizes hands-on laboratory exercises and projects through which students grasp and sharpen conceptually complex notions met across different areas in cognitive science. Examples include the relation between continuous and discrete dimensions of cognition, basic notions from the mathematics of non-linearity (attractor, bifurcation, dynamic stability), and the competence/performance distinction. The leading notions are developed in lectures and then applied and sharpened in the laboratory by students working individually or in teams. The course's programming environment is Matlab. However, this is not a how-to-program course; rather, the course uses Matlab to convey concepts and tools for processing and analysis of speech data which are relevant to the problems take up in the course.
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