Speech recognition by machines and humans
Speech Communication
Nonlinear time series analysis
Nonlinear time series analysis
A two-level drive – response model of non-stationary speech signals
NOLISP'05 Proceedings of the 3rd international conference on Non-Linear Analyses and Algorithms for Speech Processing
Non-stationary self-consistent acoustic objects as atoms of voiced speech
NOLISP'07 Proceedings of the 2007 international conference on Advances in nonlinear speech processing
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Voiced segments of speech are assumed to be composed of non-stationary acoustic objects which can be described as stationary response of a non-stationary fundamental drive (FD) process and which are furthermore suited to reconstruct the hidden FD by using a voice adapted (self-consistent) part-tone decomposition of the speech signal. The universality and robustness of human pitch perception encourage the reconstruction of a band-limited FD in the frequency range of the pitch. The self-consistent decomposition of voiced continuants generates several part-tones which can piecewise be confirmed to be topologically equivalent to corresponding acoustic modes of the excitation on the transmitter side. As topologically equivalent image of a glottal master oscillator, the self-consistent FD is suited to serve as low frequency part of the basic time-scale separation of auditive perception and to describe the broadband voiced excitation as entrained (synchronized) and/or modulated primary response. Being guided by the acoustic correlates of pitch and loudness perception, the time-scale separation avoids the conventional assumption of stationary excitation and represents the basic decoding step of an advanced precision transmission protocol of self-consistent (voiced) acoustic objects. The present study is focussed on the adaptation of the trajectories (contours) of the centre filter frequency of the part-tones to the chirp of the glottal master oscillator.