DocumentCode :
1749753
Title :
Optimal estimation of subband speech from nonuniform non-recurrent signal-driven sparse samples
Author :
Penev, Penio S. ; Iordanov, Liubomire G.
Author_Institution :
Rockefeller Univ., New York, NY, USA
Volume :
2
fYear :
2001
fDate :
2001
Firstpage :
765
Abstract :
Speech signals are comprised of auditory objects that are localized in time, but can appear anywhere in the record. We introduce a strategy for non-recurrent irregular signal-driven sampling and subsequent maximum likelihood interpolation of speech subbands that achieves object constancy-the representation of an auditory object is precisely locked to the timing of its features, but is otherwise constant. Moreover, the reconstruction fidelity can be traded flexibly for sampling rate, over a broad range of signal-to-noise ratios and application requirements. In an experiment with wideband speech, we find a regime in the rate/distortion curve that has almost perfect reconstruction at a rate substantially lower than the respective Nyquist rate
Keywords :
channel bank filters; interpolation; maximum likelihood estimation; rate distortion theory; sampling methods; speech processing; auditory objects; features timing; maximum likelihood interpolation; nonrecurrent irregular signal-driven sampling; nonuniform nonrecurrent signal-driven sparse samples; object constancy; optimal estimation; rate/distortion curve; reconstruction fidelity; sampling rate; signal-to-noise ratios; speech signals; subband speech; wideband speech; Filter bank; Interpolation; Maximum likelihood estimation; National electric code; Nonlinear filters; Nonuniform sampling; Quantization; Sampling methods; Signal to noise ratio; Speech;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on
Conference_Location :
Salt Lake City, UT
ISSN :
1520-6149
Print_ISBN :
0-7803-7041-4
Type :
conf
DOI :
10.1109/ICASSP.2001.941027
Filename :
941027
Link To Document :
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