Doctoral Dissertation Research:Modeling temporal coordination in speech production using an artificial central pattern generator neural network

University Of Illinois At Urbana-Champaign, Urbana IL

Investigators

Abstract

This project investigates how timing is coordinated in speech production and how this coordination can be computationally modeled using artificial neural networks. Research has shown that speech rhythm reflects a multi-tiered, hierarchical organization of speech units (syllables, accentual units, phrases) that are essentially cyclical in nature. One type of neural network which shares these properties, the central pattern generator (CPG), has been hypothesized to underlie speech timing. This project presents two speech production experiments designed to investigate temporal coordination within and among three levels of speech units in French and English, languages with distinct rhythm types, and to discover which timing properties they share and which are language-specific. A three-level CPG-type artificial neural network is presented which is used to model the results of both experiments in order to test the ability of such a model to simulate the timing behavior of two rhythmically distinct languages. Experiment 1 focuses on the coordination between phrases, accentual units, and syllables through a comparison of the durational effects of lengthening due to phrasal stress and phrase-final syllable lengthening in both languages. Experiment 2 compares the overall temporal coordination of spoken phrases and their constituent parts in the two languages by measuring the changes in articulatory timing of phrases which are repeated multiple times. The main goals of the proposed studies and modeling work are to investigate temporal coordination between the hierarchically structured levels of speech units, specifically how that coordination varies between languages, and to test the ability of a biologically inspired CPG-type neural network model to model this coordination and the speech patterns that result from it. This work contributes to an understanding of the coordination and timing of rhythm units in speech and how that coordination may be generated by the brain. In its broader impact, it will enable the integration of theories of speech production with other motor behavior in biological and cognitive models, and help to forge links between research on speech, linguistic prosody, and more broadly, neural models of animal behavior. This work will also contribute to the construction of a unified model of rhythm and prosody which is sufficient to explain both the underlying universalities and the variations of human language. The project will also enrich the training of the graduate student co-PI.