Task-parameterized models of movements aim at automatically adapting movements to new
situations encountered by a robot. The task parameters can, for example, take the form of …

In this paper, we describe a novel spectral conversion method for voice conversion (VC). A
Gaussian mixture model (GMM) of the joint probability density of source and target features …

This paper derives a speech parameter generation algorithm for HMM-based speech
synthesis, in which the speech parameter sequence is generated from HMMs whose …

In this paper, we describe an HMM-based speech synthesis system in which spectrum, pitch
and state duration are modeled simultaneously in a unified framework of HMM. In the …

Statistical parametric speech synthesis (SPSS) combines an acoustic model and a vocoder
to render speech given a text. Typically decision tree-clustered context-dependent hidden …

A study of digital speech processing, synthesis and recognition. This second edition
contains new sections on the international standardization of robust and flexible speech …

This paper describes a novel parameter generation algorithm for an HMM-based speech
synthesis technique. The conventional algorithm generates a parameter trajectory of static …

This paper describes an hidden Markov model (HMM)-based speech synthesizer that
utilizes glottal inverse filtering for generating natural sounding synthetic speech. In the …

This paper discusses a hidden Markov model (HMM) based on multi-space probability
distribution (MSD). The HMMs are widely-used statistical models to characterize the …

This paper presents a new text-to-speech synthesis system based on HMM which includes
dynamic features, ie, delta and delta-delta parameters of speech. The system uses triphone …