We investigate incremental word learning in a Hidden Markov Model (HMM) framework suitable for human-robot interaction. In interactive learning, the tutoring time is a crucial fac...
This paper presents a comparison between a hidden Markov model (HMM) based method and a novel artificial neural network (ANN) based method for lip synchronisation. Both model type...
As more and more information is available in the Electronic Health Record in the form of free-text narrative, there is a need for automated tools, which can process and understand...
The Student’s-t hidden Markov model (SHMM) has been recently proposed as a robust to outliers form of conventional continuous density hidden Markov models, trained by means of t...
We describe a new approach to speech recognition, in which all Hidden Markov Model (HMM) states share the same Gaussian Mixture Model (GMM) structure with the same number of Gauss...
Daniel Povey, Lukas Burget, Mohit Agarwal, Pinar A...
This paper is concerned with developing an information-theoretic framework to aggregate the state space of a Hidden Markov Model (HMM) on discrete state and observation spaces. The...
Abstract. This paper proposes an accelerometer-based gesture recognition algorithm. As a pre-process procedure, raw data output by accelerometer should be quantized, and then use d...
Chord sequences are a compact and useful description of music, representing each beat or measure in terms of a likely distribution over individual notes without specifying the not...
This paper presents a new approach for Handwritten Word Recognition based on Hidden Markov Model theory and the sliding window technique. The new approach uses specific singularit...
Sebastiano Impedovo, Anna Ferrante, Raffaele Modug...
A word in one language can be translated to zero, one, or several words in other languages. Using word fertility features has been shown to be useful in building word alignment mo...