Events Calendar

NL Seminar- Vikram Ramanarayanan: "Data-Driven Techniques for Modeling Speech Motor Control"

Speaker: Vikram Ramanarayanan , USC

Talk Title: "Data-Driven Techniques for Modeling Speech Motor Control"

Series: Natural Language Seminar

Abstract: Modeling the ways in which humans produce and perceive various forms of behavioral communication, such as speech, pose many diverse challenges. For instance, from a controls perspective, it is important to understand and model how control and coordination of various biological actuators in human body is achieved order to produce motor actions. From a signal processing perspective, we would like to discover novel representations or system architectures that are used in order to effect this coordination.

We present a computational, data-driven approach to derive interpretable movement primitives from speech articulation data in a bottom-up manner. It puts forth a convolutive Nonnegative Matrix Factorization algorithm with sparseness constraints (cNMFsc) to decompose a given data matrix into a set of spatio-temporal basis sequences and an activation matrix. The algorithm optimizes a cost function that trades off the mismatch between the proposed model and the input data against the number of primitives that are active at any given instant. We further argue that such primitives can be modeled using nonlinear dynamical systems in a control-theoretic framework for speech motor control. Specifically, we extend our approach to extract a spatio-temporal dictionary of control primitives (sequences of control parameters), which can then be used to control a dynamical systems model of the vocal tract to produce any desired sequence of movements. Although the method is particularly applied to measured and synthesized articulatory data in our case, the framework is general and can be applied to any multivariate timeseries. The results suggest that the proposed algorithm extracts movement primitives from human speech production data that are linguistically interpretable.

Biography: Home Page:

http://sail.usc.edu/~vramanar/

Host: Yang Gao

More Info: http://nlg.isi.edu/nl-seminar/

Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey

Audiences: Everyone Is Invited

Contact: Peter Zamar

Event Link: http://nlg.isi.edu/nl-seminar/