This paper presents a framework for efficient HMM-based estimation of unreliable spectrographic speech data. It discusses the role of Hidden Markov Models (HMMs) during minimum mea...
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Accurate unsupervised learning of phonemes of a language directly from speech is demonstrated via an algorithm for joint unsupervised learning of the topology and parameters of a ...
Many clustering algorithms have been proposed to partition a set of static data points into groups. In this paper, we consider an evolutionary clustering problem where the input d...
Abstract. Optical music recognition (OMR) enables librarians to digitise early music sources on a large scale. The cost of expert human labour to correct automatic recognition erro...
Laurent Pugin, John Ashley Burgoyne, Ichiro Fujina...