Behavioral models of human operators engaged in complex, time-critical high-risk domains, such as those typical in Human Supervisory Control (HSC) settings, are of great value because of the high cost of operator failure. We propose that Hidden Semi-Markov Models (HSMMs) can be employed to model behaviors of operators in HSC settings where there is some intermittent human interaction with a sys...

This paper describes spontaneous dialogue speech synthesis based on multiple-regression hidden semi-Markov model (MRHSMM), which enables users to specify paralinguistic information of synthesized speech with a dimensional representation. Paralinguistic aspects of synthesized speech are controlled by multiple regression models whose explanatory variables are abstract dimensions such as pleasant-...

This paper presents a statistical method that estimates a sequence of musical notes from a vocal F0 trajectory. Since the onset times and F0s of sung notes are considerably deviated from the discrete tatums and pitches indicated in a musical score, a score model is crucial for improving timefrequency quantization of the F0s. We thus propose a hierarchical hidden semi-Markov model (HHSMM) that c...

In speaker adaptation for HMM-based speech synthesis, model adaptation and adaptive training techniques play key roles. For reducing dependency on an initial model and adapting the model to wide-ranging target speakers, we propose speaker adaptation and adaptive training algorithms based on ESAT algorithm for HMM-based speech synthesis. The ESAT algorithm estimates contributing rate of several ...

We present an audio chord recognition system based on a generalization of the Hidden Markov Model (HMM) in which the duration of chords is explicitly considered a type of HMM referred to as a hidden semi-Markov model, or duration-explicit HMM (DHMM). We find that such a system recognizes chords at a level consistent with the state-of-the-art systems – 84.23% on Uspop dataset at the major/minor ...

In this paper, we address the problem of realtime detection of viruses docking to nanowires, especially when multiple viruses dock to the same nano-wire. The task becomes more complicated when there is an array of nanowires coated with different antibodies, where different viruses can dock to each coated nanowire at different binding strengths. We model the array response to a viral agent as a ...

In the present paper, hidden Markov model (HMM) based speech synthesis system developed in Nagoya Institute of Technology (Nitech-HTS) for a competition of text-to-speech synthesis systems using the same speech databases, named Blizzard Challenge 2005, is described. We show an overview of the basic HMM-based speech synthesis system and then recent developments to the latest one such as STRAIGHT...

In this paper we present an approach to tree recognition and localisation in orchard environments for tree-crop applications. The method builds on the natural structure of the orchard by first segmenting the data into individual trees using a Hidden Semi-Markov Model. Second, a descriptor for representing the characteristics of the trees is introduced, allowing a Hidden Markov Model based match...

This paper describes a technique for controlling voice quality of synthetic speech using multiple regression hidden semi-Markov model (HSMM). In the technique, we assume that the mean vectors of output and state duration distribution of HSMM are modeled by multiple regression with a parameter vector called voice quality control vector. We first choose three features for controlling voice qualit...

Coal mine belt conveyor can guarantee the coal mine production stable and efficient. On how to effectively predict abnormal accident occurrence time, this paper puts forward a method to predict the abnormal accident occurrence time based on Hidden Markov Model and Hidden Semi-Markov Model. Large amount of time series is collected through belt conveyor protection sensors. The corresponding HMM o...