Psycho-acoustic modeling of audio with exponentially damped sinusoids

Hermus, Kris; Verhelst, Werner; Wambacq, Patrick

doi:10.1109/icassp.2002.5744978

Cited by 3 publications

(4 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While some work has been done for extracting perceptually relevant sinusoids using MP based schemes (e.g., [31], [32]), less efforts have been directed toward estimating perceptually relevant ESM parameters using subspace techniques [21].…”

mentioning

confidence: 99%

“…In [21] an attempt is made to combine psycho-acoustic information with a subspace based ESM parameter estimation scheme. In this scheme, the signal to be modeled is divided into subbands and an independent (low-order) ESM is used for each subband.…”

mentioning

confidence: 99%

“…Furthermore, since exponentially damped sinusoids play a fundamental role in linear system theory, a vast amount of research supports the treatment of this model. The ESM has been applied to analysis and/or synthesis of audio (e.g., [18]- [21]) as well as speech signals (e.g., [22], [23]). …”

mentioning

confidence: 99%

“…The ESM components are estimated in an iterative manner, one at a time, by assigning at each iteration an additional damped sinusoid to the subband with the largest residual error-noise to masking level, in much the same way as the bits are assigned to different subbands in MPEG [24]. The approach in [21] operates at a lower computational complexity than a corresponding full-band scheme. However, it is not optimal because subbands are treated independently.…”

mentioning

confidence: 99%

See 3 more Smart Citations

A Perceptual Subspace Approach for Modeling of Speech and Audio Signals With Damped Sinusoids

Jensen

Heusdens

Jensen

2004

IEEE Trans. Speech Audio Process.

View full text Add to dashboard Cite

Abstract-The problem of modeling a signal segment as a sum of exponentially damped sinusoidal components arises in many different application areas, including speech and audio processing. Often, model parameters are estimated using subspace based techniques which arrange the input signal in a structured matrix and exploit the so-called shift-invariance property related to certain vector spaces of the input matrix. A problem with this class of estimation algorithms, when used for speech and audio processing, is that the perceptual importance of the sinusoidal components is not taken into account. In this work we propose a solution to this problem. In particular, we show how to combine well-known subspace based estimation techniques with a recently developed perceptual distortion measure, in order to obtain an algorithm for extracting perceptually relevant model components. In analysis-synthesis experiments with wideband audio signals, objective and subjective evaluations show that the proposed algorithm improves perceived signal quality considerable over traditional subspace based analysis methods.Index Terms-Complex exponentials, perceptually relevant sinusoids, psycho-acoustical distortion measure, sinusoidal modeling, speech and audio processing, subspace-based signal analysis.

show abstract

mentioning

confidence: 99%

mentioning

confidence: 99%