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- Hélène Valbret, E. Moulines, Jean-Pierre Tubach
- [Proceedings] ICASSP-92: IEEE International…
- 1992

Whereas speaker adaptation has received much attention for speech recognition few studies have been devoted to voice transformation for speech synthesis, despite the potential interests of such… (More)

Computing smoothing distributions, the distributions of one or more states conditional on past, present, and future observations is a recurring problem when operating on general hidden Markov models.… (More)

Blind separation of sources consists in recovering a set of statistically independent signals whose only mixtures are observed. Such instantaneous mixtures occur in narrow band array data which can… (More)

- Olivier Cappé, E. Moulines
- IEEE Signal Processing Letters
- 1996

Traditional spectral envelope estimation methods suffer from significant drawbacks in (high-pitched) voiced segments: spectral peaks tend to be biased toward pitch harmonics. To alleviate this… (More)

- Olivier Cappé, J. Laroche, E. Moulines
- Proceedings of Workshop on Applications of…
- 1995

This paper presents an improved method for the estimation of a continuous frequency-envelope when the value of this envelope is specified only at discrete frequencies. It is based on the Galas/Rodet… (More)

In this contribution, the statistical properties of the wavelet estimator of the long-range dependence parameter introduced in Abry et al. (1995) are discussed for a stationary Gaussian process. This… (More)

In general, the transition probability P of the Markov chain depends on some tuning parameter θ defined on some space Θ which can be either finite dimensional or infinite dimensional. The success of… (More)

An undercarriage for farm wagons and similar vehicles in which the frame of the vehicle is mounted on one or more axles by units at each end of the axles, each unit consisting of plates connected to… (More)

The forgetting of the initial distribution for discrete Hidden Markov Models (HMM) is addressed: a new set of conditions is proposed, to establish the forgetting property of the filter, at a… (More)

Multiple-try methods are extensions of the Metropolis algorithm in which the next state of the Markov chain is selected among a pool of proposals. These techniques have witnessed a recent surge of… (More)