in this paper semi-markov models are used to forecast the triple dimensions of next earthquake occurrences. each earthquake can be investigated in three dimensions including temporal, spatial and magnitude. semi-markov models can be used for earthquake forecasting in each arbitrary area and each area can be divided into several zones. in semi-markov models each zone can be considered as a state...

  In this paper Semi-Markov models are used to forecast the triple dimensions of next earthquake occurrences. Each earthquake can be investigated in three dimensions including temporal, spatial and magnitude. Semi-Markov models can be used for earthquake forecasting in each arbitrary area and each area can be divided into several zones. In Semi-Markov models each zone can be considered as a sta...

The paper examines the application of semi-Markov models to the phenomenon of earthquakes in Tehran province. Generally, earthquakes are not independent of each other, and time and place of earthquakes are related to previous earthquakes; moreover, the time between earthquakes affects the pattern of their occurrence; thus, this occurrence can be likened to semi-Markov models. ...

Article history: Received 14 April 2009 Available online 17 November 2009

Singing voice is specific in music: a vocal performance conveys both music (melody/pitch) and lyrics (text/phoneme) content. This paper aims at exploiting the advantages of melody and lyric information for real-time audio-to-score alignment of singing voice. First, lyrics are added as a separate observation stream into a template-based hidden semi-Markov model (HSMM), whose observation model is...

In this paper we apply adaptive modeling methods in Hidden Semi-Markov Model (HSMM) based speech synthesis to the modeling of three different varieties, namely standard Austrian German, one Middle Bavarian (Upper Austria, Bad Goisern), and one South Bavarian (East Tyrol, Innervillgraten) dialect. We investigate different adaptation methods like dialectadaptive training and dialect clustering th...

In this paper we discuss the most recent evaluation of the RPI language identi cation system by the National Institute of Standards and Technologies (NIST). This system is based on an acousto-phonetic approach where the phonemes present in a language are identi ed by a hidden semi-Markov model (HSMM). The HSMM was also developed at RPI. Knowledge of these phonemes provides us with the necessary...

This paper describes a technique of estimating style expressiveness for an arbitrary speaker’s emotional speech. In the proposed technique, the style expressiveness, representing how much the emotions and/or speaking styles affect the acoustic features, is estimated based on multiple-regression hidden semiMarkov model (MRHSMM). In the model training, we first train average voice model using mul...