This paper presents a method for modeling the envelope of spectral amplitude parameters of speech signals in "two dimensions" (2D). It consists of two cascaded modelings: the first one along the frequency axis is the usual cepstrum technique, which consists of modeling the log-scaled spectral envelope with a discrete cosine model (DCM). The second one, along the time axis, consists of modeling the trajectory of the envelope DCM coefficients by another similar DCM model. An iterative algorithm is proposed to optimally fit this 2D-model to the data according to a perceptual criterion based on frequency masking. This approach is shown to provide an efficient and flexible representation of spectral amplitude parameters in terms of coefficient rates, while providing good signal quality, opening new perspectives in very-low bit-rate sinusoidal speech coding.

In this paper, the problem of modeling the time-trajectory of the sinusoidal components of voiced speech signals is addressed. A new global approach is presented: a single so-called long-term (LT) model, based on discrete cosine functions, is used to model the overall trajectories of amplitude and phase parameters, for each entire voiced section of speech, differing from usual (short-term) models defined on a frame-by-frame basis. The complete analysis-modeling-synthesis process is presented, including an iterative algorithm for optimal fitting between LT model and measures. A major issue of this paper concerns the use of perceptual criteria in the LT model fitting process (both for amplitude and phase modeling). The adaptation of perceptual criteria usually defined in the short-term and/or stationary cases to the long-term processing is proposed. Experiments dealing with the ten first harmonics of voiced signals show that the proposed approach provides an efficient variable-rate representation of voiced speech signals. Promising results are given in terms of modeling accuracy, synthesis quality, and data compression. The interest of the presented approach for speech coding and speech watermarking is discussed

In this paper, the problem of modeling the trajectory of the amplitudes of speech signals is addressed within the context of the sinusoidal model of speech. A long-term model of the trajectory of the amplitude of the partials is proposed for each entire voiced section of speech, contrary to standard models, which are defined on a frame-by-frame basis. The complete analysis-modeling-synthesis process is presented. We compare a DCT-based long-term model with classical (frame-by-frame) interpolation schemes, given that the analysis process is identical in both cases. Perceptual constraints are taken into account since the distortion criterion in this approach is the level of modeling noise above the masking threshold. Promising results are given and the interest of the presented models for speech coding and watermarking applications is discussed.

Abstract In this paper, the problem of modeling the trajectory of the phase of speech signal is addressed within the context of the sinusoidal model of speech. A global or long-term model of the trajectory of the phase of the partials is proposed for each entire voiced section of speech, contrary to standard models, which are defined on a frame-by-frame basis. The complete analysis-modeling-synthesis process is presented. We compare two basic long-term models, namely a polynomial and a DCT-based model, with classical (frame-by-frame) interpolation schemes, given that the analysis process is the same in all cases. Promising results are given and the interest of the presented models for speech coding and speech watermarking applications is discussed. 1. Introduction Sinusoidal modeling of audio signals has been extensively studied since the eighties and successfully applied to a wide range of applications, such as coding or time- and frequency-stretching [1-5]. The signal is modeled as the sum of a small number