This paper explores techniques to take advantage of the fundamental difference in structure between hidden Markov models (HMM) and hierarchical hidden Markov models (HHMM). The HHMM structure allows repeated parts of the model to be merged together. A merged model takes advantage of the recurring patterns within the hierarchy, and the clusters that exist in some sequences of observations, in or...

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...

Acetylcholine (ACh) has been implicated in a wide variety of tasks involving attentional processes and plasticity. Following extensive animal studies, it has previously been suggested that ACh reports on uncertainty and controls hippocampal, cortical and cortico-amygdalar plasticity. We extend this view and consider its effects on cortical representational inference, arguing that ACh controls t...

Connected Word Recognition (CWR) is used in many applications such as voice-dialing telephone, automatic data entry, automated banking systems and, etc. This paper presents a novel architecture for CWR based on synergic Hidden Markov Model (HMM) and Dynamic Time Warping (DTW). At first, the proposed architecture eliminates obvious silent times from inputted speech utterance by preprocessing ope...

This paper describes a method for selecting an appropriate phone set in dialect speech synthesis for a so far undescribed dialect by applying hidden Markov model (HMM) based training and clustering methods. In this pilot study we show how a phone set derived from the phonetic surface can be optimized given a small amount of dialect speech training data.

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...

Robots may encounter undesirable outcomes due to failures during the execution of their plans in the physical world. Failures should be detected, and the underlying reasons should be found by the robot in order to handle these failure situations efficiently. Sometimes, there may be more than one cause of a failure, and they are not necessarily related to the action in execution. In this paper, ...