Voice morphing technology with speaker recognition enables a user to transform one person's speech pattern into another person's pattern with distinct characteristics, giving it a new identity, while preserving the original content. This is an area of numerous applications and for this reason it has been the subject of considerable research effort.Some examples of ongoing projects that will benefit from successful voice conversion techniques are:
Low-order models of the Martian atmosphere and simplified models of the QBO
The aim of this project is to generate reduced-order models suitable to study the long-term behaviour of the Martian atmospheric dynamics. At the moment we are investigating the possibilities of Proper Orthogonal Decomposition and related techniques.
We are also investigating synchronisation in simplified models for the Quasi-Biennial Oscillation, when coupled to the annular and semi-annular mode.
Comparing continuous and discrete nonlinear dynamics
This project deals with the nonlinear dynamics of electronic circuits focusing on the Moore-Spiegel equations. The study has both an experimental and analytical component. Huge data sets are generated at certain parameter values and then subjected to analysis by different tools.
This project builds on the results of two existing DPhil studies into the use of empirically determined basis functions, calculated from time series of the velocity fields to generate low order nonlinear models of more complicated baroclinic flows. These include numerical models of the Martian atmosphere in which topographic features are included, as well as laboratory models of more complicated baroclinic flows.
Predicting nonlinear systems with uncertainties: The data assimiation method
Data assimilation encompasses the techniques which utilize the information content from both the observations of the system states and the prior information (also called the background) to estimate the system states. This is an area with important applications to meteorology, geophysics, oceanography and so on. This project aims to study advanced data assimilation techniques like four dimensional variational data assimilation (4D-Var), ensemble Kalman filters (EnKFs), and investigate the factors that may affect their performances. Current work involves full waveform inversion for seismic problems.
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