The purpose of this paper is towards the algebraic study of rough finite state machines, i.e., to introduce the concept of homomorphisms between two rough finite state machines, to associate a rough transformation semigroup with a rough finite state machine and to introduce the concept of coverings of rough finite state machines as well as rough transformation semigroups.

The paper deals with training of speaker-clustered acoustic models. Various training techniques Maximum Likelihood, Discriminative Training and two adaptation based on the MAP and Discriminative MAP were tested in order to minimize an impact of speaker changes to the correct function of the recognizer when a response of the automatic cluster detector is delayed or incorrect. Such situation is v...

A function on a discrete group is weakly combable if its discrete derivative with respect to a combing can be calculated by a finite state automaton. A weakly combable function is bicombable if it is Lipschitz in both the left and right invariant word metrics. Examples of bicombable functions on word-hyperbolic groups include (1) homomorphisms to Z (2) word length with respect to a finite gener...

A function on a discrete group is weakly combable if its discrete derivative with respect to a combing can be calculated by a finite-state automaton. A weakly combable function is bicombable if it is Lipschitz in both the leftand right-invariant word metrics. Examples of bicombable functions on word-hyperbolic groups include: (1) homomorphisms to Z; (2) word length with respect to a finite gene...