An extension of the adaptive Quasi-Harmonic Model

Kafentzis, George P.; Pantazis, Yannis; Rosec, Olivier; Stylianou, Yannis

doi:10.1109/icassp.2012.6288944

Cited by 18 publications

(23 citation statements)

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“…Even so, local non-stationarity is only partially addressed in QHM. It was shown in [14] that an adaptive sinusoidal model, called adaptive Quasi-Harmonic Model (aQHM) is able to efficiently tackle local phase non-stationarity, and in [15], an extension to include amplitude non-stationarity is proposed, referred to as the extended aQHM (eaQHM). Together, we propose to be referred to as the adaptive Sinusoidal Models (aSMs), and all are achieved by estimating the frequency (and the amplitude, for eaQHM) trajectories of the deterministic part and then re-estimating the parameters using a new set of time-varying frequency (and amplitude, for eaQHM) basis functions.…”

Section: Introductionmentioning

confidence: 99%

Time-scale modifications based on a full-band adaptive harmonic model

Kafentzis

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Rosec³

et al. 2013

2013 IEEE International Conference on Acoustics, Speech and Signal Processing

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In this paper, a simple method for time-scale modifications of speech based on a recently suggested model for AM-FM decomposition of speech signals, is presented. This model is referred to as the adaptive Harmonic Model (aHM). A full-band speech analysis/synthesis system based on the aHM representation is built, without the necessity of separating a deterministic and/or a stochastic component from the speech signal. The aHM models speech as a sum of harmonically related sinusoids that can adapt to the local characteristics of the signal and provide accurate instantaneous amplitude, frequency, and phase trajectories. Because of the high quality representation and reconstruction of speech, aHM can provide high quality time-scale modifications. Informal listenings show that the synthetic time-scaled waveforms are natural and free of some common artifacts encountered in other state-of-the-art models, such as "metallic quality", chorusing, or musical noise.

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Section: Introductionmentioning

confidence: 99%

Time-scale modifications based on a full-band adaptive harmonic model

Kafentzis

Degottex

Rosec³

et al. 2013

2013 IEEE International Conference on Acoustics, Speech and Signal Processing

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“…Figure 3 shows the first and second iterations to illustrate adaptation of one sinusoid. Kafentzis et al [43] adapted both the instantaneous amplitude and the instantaneous phase ofx (n, m) with a similar iterative procedure in eaQHM. The analysis stage useŝ…”

Section: The Extended Adaptive Quasi-harmonic Model (Eaqhm)mentioning

confidence: 99%

“…whereÂ k (n, m) andΦ k (n, m) are functions of the time-varying instantaneous amplitude and phase of each sinusoid, respectively [43,45], obtained from the parameter interpolation step and defined aŝ…”

Section: The Extended Adaptive Quasi-harmonic Model (Eaqhm)mentioning

confidence: 99%

“…Adaptation improves the fit of a spectral template via an iterative least-squares (LS) parameter estimation followed by frequency correction. Later, Kafentzis [43] devised the extended adaptive Quasi-Harmonic Model (eaQHM), capable of adapting both amplitude and frequency trajectories of all sinusoids iteratively. In eaQHM, adaptation is equivalent to the iterative projection of the original waveform onto nonstationary basis functions that are locally adapted to the time-varying characteristics of the sound, capable of modeling sudden changes such as sharp attacks, transients, and instrumental noise.…”

Section: Introductionmentioning

confidence: 99%

“…AS have been used to model speech [43][44][45][46] and musical instrument sounds [25,47]. Pantazis [45,48] developed the adaptive Quasi-Harmonic Model (aQHM), which iteratively adapts the frequency trajectories of all sinusoids at the same time based on the Quasi-Harmonic Model (QHM).…”

Section: Introductionmentioning

confidence: 99%

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Full-Band Quasi-Harmonic Analysis and Synthesis of Musical Instrument Sounds with Adaptive Sinusoids

et al. 2016

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Abstract:Sinusoids are widely used to represent the oscillatory modes of musical instrument sounds in both analysis and synthesis. However, musical instrument sounds feature transients and instrumental noise that are poorly modeled with quasi-stationary sinusoids, requiring spectral decomposition and further dedicated modeling. In this work, we propose a full-band representation that fits sinusoids across the entire spectrum. We use the extended adaptive Quasi-Harmonic Model (eaQHM) to iteratively estimate amplitude-and frequency-modulated (AM-FM) sinusoids able to capture challenging features such as sharp attacks, transients, and instrumental noise. We use the signal-to-reconstruction-error ratio (SRER) as the objective measure for the analysis and synthesis of 89 musical instrument sounds from different instrumental families. We compare against quasi-stationary sinusoids and exponentially damped sinusoids. First, we show that the SRER increases with adaptation in eaQHM. Then, we show that full-band modeling with eaQHM captures partials at the higher frequency end of the spectrum that are neglected by spectral decomposition. Finally, we demonstrate that a frame size equal to three periods of the fundamental frequency results in the highest SRER with AM-FM sinusoids from eaQHM. A listening test confirmed that the musical instrument sounds resynthesized from full-band analysis with eaQHM are virtually perceptually indistinguishable from the original recordings.

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