An α-automaton (for α some ordinal) is an automaton similar to a Muller automaton that processes words of length α. A structure is called α-automatic if it can be presented by α-automata (completely analogous to the notion of automatic structures which can be presented by the well-known finite automata). We call a structure ordinal-automatic if it is α-automatic for some ordinal α. We continue ...

In standard generative approaches, word-formation rules contain, among other things, information on the semantics of the suffix and the syntactic category (or word-class) of possible bases. Based on the general assumption that word-class specification of the input is a crucial ingredient of derivational morphology, far-reaching claims have been made. For example, the unitary base hypothesis (Ar...

We introduce a combinatorial optimization framework that naturally yields a class of optimal word permutations. Our framework provides the first formal quantification of the intuitive idea that the longer the context shared by two symbols in a word, the closer those symbols should be to each other in a linear order of the symbols. The Burrows and Wheeler transform [6], and the compressible part...

In this paper, the automatic labeling of semantic roles in a sentence is considered as a chunking task. We define a semantic chunk as the sequence of words that fills a semantic role defined in a semantic frame. It is straightforward to convert chunking into a tagging task using one of several IOB representations. Using this representation each word is tagged with I, which means that the word i...

How to fuse static and dynamic information is a key issue in event analysis. In this paper, we present a novel approach to combine appearance and motion information together through a top-down manner for event recognition in real videos. Unlike the conventional bottom-up way, attention can be focused volitionally on top-down signals derived from task demands. A video is represented by a collect...

Automatic identification of related words and automatic detection of word senses are two long-standing goals of researchers in natural language processing. Word class information and word sense identification may enhance the performance of information retrieval systems. Large online corpora and increased computational capabilities make new techniques based on corpus linguistics feasible. Corpus...

We propose a method to construct a phrase class n-gram model for Kana-Kanji Conversion by combining phrase and class methods. We use a word-pronunciation pair as the basic prediction unit of the language model. We compared the conversion accuracy and model size of a phrase class bi-gram model constructed by our method to a tri-gram model. The conversion accuracy was measured by F measure and mo...

conclusions the findings of this study indicate that the frequency of disfluencies was increased in difficult syllable structures in comparison to simple syllable structures. according to the results, it seems that certain linguistic features, such as syllable structure can affect speech-motor output in people who stutter through affecting phonological encoding. background stuttering is one of ...