A non-parametric method for texture synthesis is proposed. The texture synthesis process grows a new image outward from an initial seed, one pixel at a time. A Markov random field model is assumed, and the conditional distribution of a pixel given all its neighbors synthesized so far is estimated by querying the sample image and finding all similar neighborhoods. The degree of randomness is con...

In this paper, we proposed a parametric model based facial animation synthesis. In the proposed algorithm various facial expressions are generated using the parametric models and the novelty of the algorithm is that new expressions can be generated by blending selected expressions. A complete parameterized model for faces would allow the animator to create any facial image by specifying the app...

We investigate parameter synthesis in the context of temporalepistemic logic. We introduce CTLPK, a parametric extension to the branching time temporal-epistemic logic CTLK with free variables representing groups of agents. We give algorithms for automatically synthesising the groups of agents that make a given parametric formula satisfied. We discuss an implementation of the technique on top o...

Interval Markov Chains (IMCs) are the base of a classic probabilistic specification theory introduced by Larsen and Jonsson in 1991. They are also a popular abstraction for probabilistic systems. In this paper we study parameter synthesis for a parametric extension of Interval Markov Chains in which the endpoints of intervals may be replaced with parameters. In particular, we propose constructi...

Statistical parametric, especially Hidden Markov Model-based, text-tospeech (TTS) synthesis has received much attention recently. The quality of HMM-based speech synthesis approaches that of the state-of-the-art unit selection systems and possesses numerous favorable features, e.g. small runtime footprint, speaker interpolation, speaker adaptation. This paper presents the improvements of a Hung...

In the last decade there has been a shift towards development of speech synthesizer using concatenative synthesis technique instead of parametric synthesis. There are a number of different methodologies for concatenative synthesis like TDPSOLA, PSOLA, and MBROLA. This paper, describes a concatenative speech synthesis system based on Epoch Synchronous Non Over Lapp Add (ESNOLA) technique, for st...

State-of-the-art text-to-speech (TTS) synthesis is often based on statistical parametric methods. Particular attention is paid to hidden Markov model (HMM) based text-to-speech synthesis. HMM-TTS is optimized for ideal voices and may not produce high quality synthesized speech with voices having frequent non-ideal phonation. Such a voice quality is irregular phonation (also called as glottaliza...

A synthetic voice personifies the system using it. In this work we examine the impact text content, voice quality and synthesis system have on the perceived personality of two synthetic voices. Subjects rated synthetic utterances based on the Big-Five personality traits and naturalness. The naturalness rating of synthesis output did not correlate significantly with any Big-Five characteristic e...

Parametric speech synthesis techniques depend on full context acoustic models generated by language front-ends, which analyse linguistic and phonetic structure. HTS, the leading parametric synthesis system, can use a number of different front-ends to generate full context models for synthesis and training. In this paper we explore the use of a new text processing front-end that has been added t...

Background: Skeletal muscle mass, which is regulated by a balance between muscle protein synthesis and degradation, is an important factor for movement to meet everyday needs, especially in pathological conditions and aging. The purpose of the present investigation was to compare the alterations of the gene expression involved in muscle protein synthesis and degradation signaling pathways induc...