ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing
DOI: 10.1109/icassp.1985.1168384
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Perceptually based linear predictive analysis of speech

Abstract: A novel speech analysis method which uses several established psychoacoustic concepts. the perceptually based linear predictive analysis (PLP), nedels the auditory spectrum by the spectrum of the low-order all-pole model. The auditory spectrum is derived from the speech waveform by critical-band filtering. equal-loudness curve pre-emphasis. and intensityloudness root compression. we demonstrate through analysis of both synthetic and natural speech that psychoacoustic concepts of spectral auditory integration i… Show more

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Cited by 63 publications
(27 citation statements)
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“…The LPC coefficients are calculated over the critical band energies of a single frame, which is followed by the transformation of the LPC coefficients to cepstral values. In [7], PLP speech analysis was first introduced as a method to represent speech signals with respect to the human perception and with as few parameters as possible. However, PLP was, as most of the other analysis techniques, sensitive towards steady-state spectral factors caused by transmission channels, such as telephone recordings or the usage of different microphones [8].…”
Section: Relative Spectral Perceptual Linear Predictive Coding (Rastamentioning
confidence: 99%
“…The LPC coefficients are calculated over the critical band energies of a single frame, which is followed by the transformation of the LPC coefficients to cepstral values. In [7], PLP speech analysis was first introduced as a method to represent speech signals with respect to the human perception and with as few parameters as possible. However, PLP was, as most of the other analysis techniques, sensitive towards steady-state spectral factors caused by transmission channels, such as telephone recordings or the usage of different microphones [8].…”
Section: Relative Spectral Perceptual Linear Predictive Coding (Rastamentioning
confidence: 99%
“…The majority of SD systems use Mel-Frequency Cepstral Coefficients (MFCC) as front-end features, although other feature spaces have been proposed, such as Linear Frequency Cepstral Coefficients (LFCC) and Perceptual Linear Predictive (PLP), (Hermansky et al, 1985). Some systems utilize prosodic features to augment the cepstral representation (see Friedland et al (2009)) while other approaches attempt to fuse several spaces and increase the diarization accuracy, (Gupta et al, 2007).…”
Section: Front-end Features and Preprocessing Stepsmentioning
confidence: 99%
“…It is well established that feature extraction methods for ASR need to take into account properties of the HAS to a certain extent: the well-known Mel-Frequency Cepstral Coefficients (MFCC) [1], for example, result from non-linear transformations of the frequency domain that mimic Fletcher's psychophysical transfer function [2], and include a triangular Also widespread, Perceptually-based Linear Prediction (PLP) [3] is a pragmatic approach to model the auditory periphery that includes: resampling for frequency warping, barkscale filter-bank, limited frequency resolution, pre-emphasis according to the threshold of hearing, amplitude compression and smoothing using linear prediction. The computational complexity of PLP feature extraction is similar to MFCC and sometimes provides better recognition accuracy.…”
Section: Introductionmentioning
confidence: 99%