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

Abstract

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.

A uniform phase representation for the harmonic model in speech synthesis applications

“…Thus, any processing ofφ i,h is better conditioned than a processing of the raw instantaneous phase value φ i,h . This property explains the success of the simple processing techniques presented in [17,18]. In [16], the relative phases were then interpolated on a continuous time axis using splines, i.e.,φ i,h ⇒ φ h (t).…”

“…These models have been widely used for speech analysis, resynthesis, and modification [12][13][14]. Sinusoidal models have evolved over the years [3,15], and recently, the so-called adaptive Harmonic Model (aHM) [16] has also been shown to yield practically transparent analysis/resynthesis and excellent modification performance [17,18]. Despite the inherent assumption that speech can be represented only by http://asmp.eurasipjournals.com/content/2014/1/38 harmonic sinusoidal components, even in unvoiced segments, aHM succeeds at capturing the relevant spectral information and noisy nature of a speech signal and thus, representing the speech signal in a uniform way, without using any voicing decision.…”

Speech Analysis and Synthesis with a Computationally Efficient Adaptive Harmonic Model

“…These models can be used for speech modeling [1], speech coding and synthesis [2], [3], voice transformation [4], speech enhancement [5] for hearing aids [6]. The parameters computed can be used to build higher-level representations [7] (e.g.…”

Adaptive sinusoidal models for speech with applications in speech modifications and audio analysis

“…For pitch scaling, the estimation of a spectral magnitude envelope is necessary, but no phase envelope estimation is followed, thus significantly simplifying modification. Part of this work has been published in ICASSP 2013 [KDRS13] and in ICASSP 2014 [KDRS14].…”

“…However, for the phase, the process is not straightforward because of its rotation due to the time advance across time instants. Therefore, it is proposed to remove this effect using the integral of kf 0 from the start of the signal, and obtain the relative phase -RP [DS13,KDRS13]. Thus, by assuming that the shape of the signal is changing smoothly, the phase values change also smoothly from one analysis time instant to the other.…”