Designed to safely share the same workspace as humans and assist them in various tasks, the new collaborative robots are targeting manufacturing and service applications that once were considered unattainable. The large diversity of tasks to carry out, the unstructured environments, and the close interaction with humans call for collaborative robots to seamlessly adapt their behaviors, so as to...

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 ...

Several types of Semi-Continuous HMM (SC-HMM) have been compared with the Continuous Density HMM (CD-HMM) in the context of Speaker Independent Isolated Words Recognition (SI-IWR). It is demonstrated that for the ten-digit vocabulary (TIDIGITS), the SC-HMM outperforms the CD-HMM when memory constraints are imposed on the system. SC-HMMs demonstrate recognition rate of about 95% with a total of ...

Cognition is a complex and dynamic process. It is an essential goal to estimate latent attentional states based on behavioral measures in many sequences of behavioral tasks. Here, we propose a probabilistic modeling and inference framework for estimating the attentional state using simultaneous binary and continuous behavioral measures. The proposed model extends the standard hidden Markov mode...

We investigate models for animal feeding behaviour, with the aim of improving understanding of how animals organise their behaviour in the short term. We consider three classes of model: hidden Markov, latent Gaussian and semi-Markov. Each can predict the typical 'clustered' feeding behaviour that is generally observed, however they differ in the extent to which 'memory' of previous behaviour i...

High-performance control of semi-Markov jump linear systems requires an accurate model for theunderlying stochastic jump process. In practice, however, a reasonable compromise between the controlquality and computational costs should be made and the tractability of the control design problem hasto be established. This paper considers the problem of finite-horizon optimal quadratic c...

Linear discriminant or Karhunen-Lo eve transforms are established techniques for mapping features into a lower dimensional subspace. This paper introduces a uniform statistical framework, where the computation of the optimal feature reduction is formalized as a Maximum-Likelihood estimation problem. The experimental evaluation of this suggested extension of linear selection methods shows a slig...

This paper describes the use of a multiple codebook SCHMM speaker verification system, which uses a novel technique for discriminative hidden Markov modelling known as discriminative observation probabilities (DOP). DOP can easily be added to a multiple codebook HMM system and require minimal additional computation and no additional training. The DOP technique can be applied to both speech and ...

In this paper, we consider the survival probability for a discrete semi-Markov risk model, which assumes individual claims are influenced by a Markov chain with finite state space and there is autocorrelation among consecutive claim sizes. Our semi-Markov risk model is similar to the one studied in Reinhard and Snoussi [1, 2] without the restriction imposed on the distributions of the claims. I...