the input transitions at t = t 1 and t = f Z imply a pulse at the input port Il of the component. The mechanism is illustrated through an example presented subsequently. ns and the input signals at ports A and B. Although both of the input signals at A and B are logical 1 and 2 ns in width that is much larger than t p / h = 0.5 ns, the overlapping region where both inputs are high constitutes a...

Probabilistic model-checking aims to prove whether a Markov decision process (MDP) satisfies temporal logic specification. The underlying methods rely on an often unrealistic assumption that the MDP is precisely known. Consequently, parametric MDPs (pMDPs) extend with transition probabilities are functions over unspecified parameters. parameter synthesis problem compute instantiation of these p...

The emerging MPEG-4 standard supports the transmission and composition of facial animation with natural video. The new standard will include a facial animation parameter (FAP) set that is defined based on the study of minimal facial actions and is closely related to muscle actions. The FAP set enables model-based representation of natural or synthetic talking-head sequences and allows intelligi...

In order to enable face animation on the Internet using high quality synthetic speech, the Text-to-Speech (TTS) servers need to be implemented on network-based servers and shared by many users. The output of a TTS server is used to animate talking heads as defined in MPEG-4. The TTS server creates two sets of data: audio data and Phonemes with optional Facial Animation Parameters (FAP) like smi...

We propose the autoregressive HMM for speech synthesis. We show that the autoregressive HMM supports efficient EM parameter estimation and that we can use established effective synthesis techniques such as synthesis considering global variance with minimal modification. The autoregressive HMM uses the same model for parameter estimation and synthesis in a consistent way, in contrast to the stan...

We present a formulation of the autoregressive HMM for speech synthesis and compare it to the standard HMM synthesis framework and the trajectory HMM. We give details of how to do efficient parameter estimation and synthesis with the autoregressive HMM and discuss consequences of the autoregressive HMM model. There are substantial similarities between the three models, which we explore. The adv...