Selected time-delay embedded speech signals. Time-delay embedded discrete-time signals from (a) one normal (JMC1NAL) and (b) one disordered (JXS01AN) speech signal from the Kay Elernetrics database. For clarity only a small section is shown (1500 samples). The embedding dimension is m = 3 and the time delay is τ = 7 samples.
In this study, in order to directly characterise the two main biophysical factors of disordered voices: increased nonlinear, complex aperiodicity and non-Gaussian, aeroacoustic breath noise, we have introduced recurrence and scaling analysis methods. We introduced a new, combined nonlinear/stochastic signal model of speech production that is capable, in principle, of producing the wide variation in behaviour of normal and disordered voice examples. To exploit the output of this model in practice, and hence all types of normal and disordered voices, we explored the use of two nonlinear measures: the recurrence period density entropy and detrended fluctuation analysis.
Discrete-Time Speech Signal Processing: Principles And Practice Download Pdf
The aim of the module is to acquaint students with the principles and practice of digital communications - from the fundamental basis of communication to how signals are represented and processed.This module is only available to students in the second year of their degree and is not available as an unusual option to students in other years of study.
The aim of the module is to acquaint students with the principles and practice of digital communications - from the fundamental basis of communication to how signals are represented and processed.The module develops an analytical approach to problems in communication design and operation, grounded in elements of communication theory sufficient to give students an understanding of the problems that affect its reliability and efficiency.It introduces the theory and implementation of digital signal processing approaches, including the representation of signals in communication systems, filtering techniques and the applications of digital signal processing.
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