Research into human perception of consonants has identified phoneme-specific perceptual cues. It has also been shown that the characteristics of the speech signal most useful for recognition depend on the specific speech sound. Typical ASR features and recognisers however neither vary with the type of sound nor relate directly to perceptual cues. We investigate classification and decoding of no...

Territorial control is a key aspect shaping the dynamics of civil war. Despite its importance, we lack data on territorial control that are fine-grained enough to account for subnational spatio-temporal variation and that cover a large set of conflicts. To resolve this issue, we propose a theoretical model of the relationship between territorial control and tactical choice in civil war and outl...

This paper describes research in progress on two quite different ways of training systems that are composed of many small Hidden Markov Models (HMM’s). The first is a purely discriminative method in which all of the parameters of all the HMM’s are adjusted to optimize classification performance. The second is an unsupervised method in which many little HMM’s are used to model the probability de...

This paper presents a novel hybrid modeling technique that is used for the first time in Hidden Markov Modelbased handwriting recognition. This new approach combines the advantages of discrete and continuous Markov models and it is shown that this is especially suitable for modeling the features typically used in handwriting recognition. The performance of this hybrid technique is demonstrated ...

The theory of behavioral communication for humanoid robots that in teract with humans is discussed in this paper For behavioral communication it is fundamental for a humanoid robot to recognize the meaning of the whole body mo tion of a human According to the previous works it can be done in the symbolic level by adopting the proto symbol space de ned by the Hidden Markov Models based on the mi...

The paper introduces an input-driven generative model for tree-structured data that extends the bottom-up hidden tree Markov model with non-homogenous transition and emission probabilities. The advantage of introducing an input-driven dynamics in structured-data processing is experimentally investigated. The results of this preliminary analysis suggest that input-driven models can capture more ...

This paper proposes a novel method for jointly estimating the track of a moving object and the events in which it participates. The method is intended for dealing with generic objects that are hard to localise and track with the performance of current detection algorithms our focus is on events involving carried objects. The tracks for other objects with which the target object interacts (e.g. ...

Today, maintenance strategies and their analyses remain a worrying problem for companies. Our study, presented in this paper, shows that our indicator can provide help for expert decision (maintenance manager) in the context of condition-based maintenance. The paper deals with the proposition of using Hidden Markov Models to track and estimate the degradation of a system, according to observati...